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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Meng Zhang; Madhuri Sankaranarayanapillai; Jingcheng Du; Yang Xiang; +5 Authors

    Abstract Background With more clinical trials are offering optional participation in the collection of bio-specimens for biobanking comes the increasing complexity of requirements of informed consent forms. The aim of this study is to develop an automatic natural language processing (NLP) tool to annotate informed consent documents to promote biorepository data regulation, sharing, and decision support. We collected informed consent documents from several publicly available sources, then manually annotated them, covering sentences containing permission information about the sharing of either bio-specimens or donor data, or conducting genetic research or future research using bio-specimens or donor data. Results We evaluated a variety of machine learning algorithms including random forest (RF) and support vector machine (SVM) for the automatic identification of these sentences. 120 informed consent documents containing 29,204 sentences were annotated, of which 1250 sentences (4.28%) provide answers to a permission question. A support vector machine (SVM) model achieved a F-1 score of 0.95 on classifying the sentences when using a gold standard, which is a prefiltered corpus containing all relevant sentences. Conclusions This study provides the feasibility of using machine learning tools to classify permission-related sentences in informed consent documents.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ BMC Bioinformaticsarrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    BMC Bioinformatics
    Article . 2023
    Data sources: DOAJ
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    BMC Bioinformatics
    Article . 2023 . Peer-reviewed
    License: CC BY
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ BMC Bioinformaticsarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      BMC Bioinformatics
      Article . 2023
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      BMC Bioinformatics
      Article . 2023 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Joel, Zirkle; Xiaomei, Han; Rebecca, Racz; Mohammadreza, Samieegohar; +4 Authors

    Abstract Background During drug development, it is essential to gather information about the change of clinical exposure of a drug (object) due to the pharmacokinetic (PK) drug-drug interactions (DDIs) with another drug (precipitant). While many natural language processing (NLP) methods for DDI have been published, most were designed to evaluate if (and what kind of) DDI relationships exist in the text, without identifying the direction of DDI (object vs. precipitant drug). Here we present a method for the automatic identification of the directionality of a PK DDI from literature or drug labels. Methods We reannotated the Text Analysis Conference (TAC) DDI track 2019 corpus for identifying the direction of a PK DDI and evaluated the performance of a fine-tuned BioBERT model on this task by following the training and validation steps prespecified by TAC. Results This initial attempt showed the model achieved an F-score of 0.82 in identifying sentences as containing PK DDI and an F-score of 0.97 in identifying object versus precipitant drugs in those sentences. Discussion and conclusion Despite a growing list of NLP methods for DDI extraction, most of them use a common set of corpora to perform general purpose tasks (e.g., classifying a sentence into one of several fixed DDI categories). There is a lack of coordination between the drug development and biomedical informatics method development community to develop corpora and methods to perform specific tasks (e.g., extract clinical exposure changes due to PK DDI). We hope that our effort can encourage such a coordination so that more “fit for purpose” NLP methods could be developed and used to facilitate the drug development process.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ BMC Bioinformaticsarrow_drop_down
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    BMC Bioinformatics
    Article . 2023
    Data sources: DOAJ
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    BMC Bioinformatics
    Article . 2023 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ BMC Bioinformaticsarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      BMC Bioinformatics
      Article . 2023
      Data sources: DOAJ
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      BMC Bioinformatics
      Article . 2023 . Peer-reviewed
      License: CC BY
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Maryam Gholipour; Reza Khajouei; Parastoo Amiri; Sadrieh Hajesmaeel Gohari; +1 Authors

    Abstract Background Extracting information from free texts using natural language processing (NLP) can save time and reduce the hassle of manually extracting large quantities of data from incredibly complex clinical notes of cancer patients. This study aimed to systematically review studies that used NLP methods to identify cancer concepts from clinical notes automatically. Methods PubMed, Scopus, Web of Science, and Embase were searched for English language papers using a combination of the terms concerning “Cancer”, “NLP”, “Coding”, and “Registries” until June 29, 2021. Two reviewers independently assessed the eligibility of papers for inclusion in the review. Results Most of the software programs used for concept extraction reported were developed by the researchers (n = 7). Rule-based algorithms were the most frequently used algorithms for developing these programs. In most articles, the criteria of accuracy (n = 14) and sensitivity (n = 12) were used to evaluate the algorithms. In addition, Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT) and Unified Medical Language System (UMLS) were the most commonly used terminologies to identify concepts. Most studies focused on breast cancer (n = 4, 19%) and lung cancer (n = 4, 19%). Conclusion The use of NLP for extracting the concepts and symptoms of cancer has increased in recent years. The rule-based algorithms are well-liked algorithms by developers. Due to these algorithms' high accuracy and sensitivity in identifying and extracting cancer concepts, we suggested that future studies use these algorithms to extract the concepts of other diseases as well.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ BMC Bioinformaticsarrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    BMC Bioinformatics
    Article . 2023
    Data sources: DOAJ
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    BMC Bioinformatics
    Article . 2023 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ BMC Bioinformaticsarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      BMC Bioinformatics
      Article . 2023
      Data sources: DOAJ
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      BMC Bioinformatics
      Article . 2023 . Peer-reviewed
      License: CC BY
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Haitham A, Elmarakeby; Pavel S, Trukhanov; Vidal M, Arroyo; Irbaz Bin, Riaz; +3 Authors

    Abstract Background Longitudinal data on key cancer outcomes for clinical research, such as response to treatment and disease progression, are not captured in standard cancer registry reporting. Manual extraction of such outcomes from unstructured electronic health records is a slow, resource-intensive process. Natural language processing (NLP) methods can accelerate outcome annotation, but they require substantial labeled data. Transfer learning based on language modeling, particularly using the Transformer architecture, has achieved improvements in NLP performance. However, there has been no systematic evaluation of NLP model training strategies on the extraction of cancer outcomes from unstructured text. Results We evaluated the performance of nine NLP models at the two tasks of identifying cancer response and cancer progression within imaging reports at a single academic center among patients with non-small cell lung cancer. We trained the classification models under different conditions, including training sample size, classification architecture, and language model pre-training. The training involved a labeled dataset of 14,218 imaging reports for 1112 patients with lung cancer. A subset of models was based on a pre-trained language model, DFCI-ImagingBERT, created by further pre-training a BERT-based model using an unlabeled dataset of 662,579 reports from 27,483 patients with cancer from our center. A classifier based on our DFCI-ImagingBERT, trained on more than 200 patients, achieved the best results in most experiments; however, these results were marginally better than simpler “bag of words” or convolutional neural network models. Conclusion When developing AI models to extract outcomes from imaging reports for clinical cancer research, if computational resources are plentiful but labeled training data are limited, large language models can be used for zero- or few-shot learning to achieve reasonable performance. When computational resources are more limited but labeled training data are readily available, even simple machine learning architectures can achieve good performance for such tasks.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ BMC Bioinformaticsarrow_drop_down
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    BMC Bioinformatics
    Article . 2023 . Peer-reviewed
    License: CC BY
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    BMC Bioinformatics
    Article . 2023
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ BMC Bioinformaticsarrow_drop_down
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      BMC Bioinformatics
      Article . 2023 . Peer-reviewed
      License: CC BY
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      BMC Bioinformatics
      Article . 2023
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    Authors: Nikitha Karkera; Sathwik Acharya; Sucheendra K. Palaniappan;

    Abstract Background The growing recognition of the microbiome’s impact on human health and well-being has prompted extensive research into discovering the links between microbiome dysbiosis and disease (healthy) states. However, this valuable information is scattered in unstructured form within biomedical literature. The structured extraction and qualification of microbe-disease interactions are important. In parallel, recent advancements in deep-learning-based natural language processing algorithms have revolutionized language-related tasks such as ours. This study aims to leverage state-of-the-art deep-learning language models to extract microbe-disease relationships from biomedical literature. Results In this study, we first evaluate multiple pre-trained large language models within a zero-shot or few-shot learning context. In this setting, the models performed poorly out of the box, emphasizing the need for domain-specific fine-tuning of these language models. Subsequently, we fine-tune multiple language models (specifically, GPT-3, BioGPT, BioMedLM, BERT, BioMegatron, PubMedBERT, BioClinicalBERT, and BioLinkBERT) using labeled training data and evaluate their performance. Our experimental results demonstrate the state-of-the-art performance of these fine-tuned models ( specifically GPT-3, BioMedLM, and BioLinkBERT), achieving an average F1 score, precision, and recall of over $$>0.8$$ > 0.8 compared to the previous best of 0.74. Conclusion Overall, this study establishes that pre-trained language models excel as transfer learners when fine-tuned with domain and problem-specific data, enabling them to achieve state-of-the-art results even with limited training data for extracting microbiome-disease interactions from scientific publications.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ BMC Bioinformaticsarrow_drop_down
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    BMC Bioinformatics
    Article . 2023 . Peer-reviewed
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    BMC Bioinformatics
    Article . 2023
    Data sources: DOAJ
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ BMC Bioinformaticsarrow_drop_down
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      BMC Bioinformatics
      Article . 2023 . Peer-reviewed
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      BMC Bioinformatics
      Article . 2023
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    Authors: Muhammet İkbal Bakır;

    Bu makale Hegel felsefesini temel alarak özne kavramını ele almaya çalışıyor. Genel olarak Hegel’in bize önerdiği özneyi, klasik felsefedeki özne kavrayışından oldukça farklı bir yerde buluyor. Bu yeni kavrayış, özneyi bir sabitlik ve kendine eşitlik olarak düşünmüyor; bunun yerine özneyi sürekli kendine dönen bir hareket olarak düşünüyor. Öznenin bir hareket olarak düşünülmesini ise daha çok çatallanma ve dolayım kavramlarından itibaren anlamaya çalışıyor. Bundan başka; bu makale, Hegelci özne yapısı içinde kalarak Hegelci özneyi eleştirmeye çalışıyor ve onun ötesinde bir özne kavrayışı sunmaya çalışıyor. Bu eleştiri ve önerinin temel kavramlarını ise ‘ayrık özne’, ‘gömülü özne’, ruh ve insan kavramları teşkil ediyor. This article tries to deal with the concept of the subject based on Hegel's philosophy. In general, Hegel's conception of the subject is quite different from the conception of the subject in classical philosophy. This new conception does not think of the subject as a fixity and equality to itself; instead, it thinks of the subject as a movement that constantly returns to itself. He tries to understand the conception of the subject as a movement from the concepts of bifurcation and mediation. Furthermore, this article tries to criticize the Hegelian subject by staying within the Hegelian subject structure and tries to offer a conception of the subject beyond it. The basic concepts of this critique and proposal are the concepts of 'cynical subject', 'embedded subject', soul and human being.

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    İbn Haldun Çalışmaları Dergisi
    Article . 2023 . Peer-reviewed
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      İbn Haldun Çalışmaları Dergisi
      Article . 2023 . Peer-reviewed
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    Authors: Mevlan Tanrıkut;

    The Reign of Xi Jinping has been characterized as assertive, unapologetic, and autocratic both at home and abroad(So, 2019). His strict control over Chinese companies and cracking down on private high-tech companies have become debated. If we look back economic system of the Chinese Communist Party, we will find that state control of the economy has been the primary trend. One might ask, what are the reasons for the Chinese Communist Party, particularly Xi Jinping’s sensitiveness to private business, and where has the idea of state monopoly over the private sector originated? By highlighting the importance of the historical approach, rather than a progressive one, for analyzing the statecraft in contemporary China methodologically, the present paper tries to address this question by examiningthe Discourses on Salt and Iron, a famous classic piece recorded by Huan Kuan of the Han Dynasty (202 BC –220 AD) and its legacy in successive governments. The first part of the paper focuses on the historical background of the Chinese state monopoly, which aims to show the historical event that led to the implementation of monopolistic economic policies and supportive rational arguments for its continuation. The second part sheds light on the continuation of this policy and illustrates howand why this policy is still alive today. By pondering above all, this study argues that China’s main concern in the economy is maintaining the power gap between the authority and private merchants, which is the legacy of traditional Chinese statecraft. Xi Jinping yönetimi, ulusal ve uluslararası düzeyde iddialı, özür dilemeyen ve otokratik olarak nitelendirilmektedir. Çinli şirketler üzerindeki sıkı kontrol ve yüksek teknoloji şirketlerine yönelik baskılar geniş çapta tartışmalara konu olmaktadır. Çin Komünist Partisi'nin ekonomik sistemine bakıldığında da, devlet kontrolünün temel bir eğilim olduğu görülmektedir. Xi'in özel sektöre olan hassasiyetinin nedeni ve özel sektör üzerinde devlet tekeli fikri, sorulabilecek önemli sorulardır. Bu makale, Çağdaş Çin'deki devlet yönetimini ilerici bir metodoloji yerine tarihsel bir yaklaşımla inceleyerek, Tuz ve Demir Üzerine Söylevler adlı ünlü klasik eserin ana fikiri ve onun ardışık hükümetlerdeki mirasını analiz ederek bu sorulara cevap aramaktadır. İlk bölüm tarihsel bir perspektifle, tekelci ekonomi politikalarının tarihsel arka planı bu politikayı destekleyici rasyonel argümanları göstermeyi odaklanmaktadır. İkinci bölüm ise bu politikanın günümüzde nasıl ve neden hala canlı olduğunu açıklamaya çalışmaktadır. Bunları analız derek bu çalışma, Çin'in ekonomideki ana endişesinin, geleneksel Çin devlet yönetiminin mirası olan otorite ile özel sektör arasındaki güç farkını korumak olduğunu savunmaktadır.

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    İbn Haldun Çalışmaları Dergisi
    Article . 2023 . Peer-reviewed
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      İbn Haldun Çalışmaları Dergisi
      Article . 2023 . Peer-reviewed
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    Authors: Mohammad Javid Fedayee;

    This article is a study of the social and political works of Ibn Khaldun, a famous 14th-century Muslim historian, philosopher, and scholar. His insights into the field of social dynamics of international relations were widely acclaimed and still influence current scholars. Ibn Khaldun's methodof history was distinctive, which is emphasizing how social institutions and human behavior shaped historical facts. The Muqqddima, his seminal work, offered a thorough examination of the cycles and patterns of human behavior and the evolution of society,especially in the area of international relations. Ibn Khaldun's Asabiya, Umran, Rural and Urban life, State, and Power are his most fascinating works, and his Umran can be considered a universal civilization. His concepts still help us understand the complexity of human behavior and social development, especially in international relations. Bu makale, 14. yüzyılda yaşamış ünlü Müslüman tarihçi, filozof ve akademisyen İbn Haldun'un sosyal ve siyasi eserleri üzerine bir çalışmadır. Uluslararası ilişkilerin sosyal dinamikleri alanındaki görüşleri büyük beğeni toplamış ve günümüz akademisyenlerini hala etkilemektedir. İbn Haldun'un tarih metodu, sosyal kurumların ve insan davranışlarının tarihsel olguları nasıl şekillendirdiğini vurgulayan kendine özgü bir metottur. İbn Haldun'un ufuk açıcı eseri Mukaddime, özellikle uluslararası ilişkiler alanında insan davranışının döngüleri ve kalıpları ile toplumun evriminin kapsamlı bir incelemesini sunmuştur. İbn Haldun'un Asabiye, Umran, kırsal ve kentsel yaşam, devlet ve iktidar en etkileyici eserleridir ve Umran'ı evrensel bir medeniyet olarak kabul edilebilir. Onun kavramları, özellikle uluslararası ilişkilerde insan davranışının ve sosyal gelişimin karmaşıklığını anlamamıza hala yardımcı olmaktadır.

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    İbn Haldun Çalışmaları Dergisi
    Article . 2023 . Peer-reviewed
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      İbn Haldun Çalışmaları Dergisi
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    Authors: Ekrem Erden; Sefa Bulut;

    Son yıllarda yaşanan teknolojik gelişmeler, teknolojik cihazların artan üretimi ve yaygınlaşması, dijital cihazlara erişimi kolaylaştırmıştır. Artık günlük yaşamın birçok alanında vazgeçilmez haline gelen dijital araçların eğlence alanında da aynı konuma geldiği söylenebilir. Dijital oyunlar günümüzde yaygın bir şekilde her yaş grubundaki insan tarafından oynanmaktadır. Ancak ilkokul ve ortaokul çağındaki öğrenciler bu oyunların ilk sırada gelen tüketicileri arasındadır. Dijital oyunların bağımlılık yapma potansiyeli ise yapılan çalışmalar tarafından ortaya konulmuştur. Dijital oyun bağımlılığının, birçok problemin yanında yalnızlığa yol açabileceği bilinmektedir. Bu çalışma, ilkokul ve ortaokul öğrencilerinin dijital oyun bağımlılıkları ve yalnızlık arasındaki ilişki ile ilgili yapılan çalışmaları incelemek ve konuyu genel hatlarıyla tartışmak amacıyla yapılmıştır. Dijital oyun bağımlılığının tanımı ve kriterleri, etiyolojisi, kız ve erkek öğrenciler arasındaki farklılıklar, yalnızlık, koruyucu faktörler verisk faktörleri güncel araştırmalar ışığında tartışılmış ve ailelere öneriler sunulmuştur. Konuyla ilgili araştırmaların incelenmesi sonucunda dijital oyun bağımlısı olan ilkokul ve ortaokul öğrencilerinin yalnızlık düzeylerinin daha yüksek olduğu sonucuna ulaşılmıştır. Technological developments in recent years, increased production, and the proliferation of technological devices have facilitated to reach digital devices. It is possible to say that digital devices that have become indispensable in many areas of daily life have attained the same location in the entertainment field. Digital games are widely played by people of all age groups today, but primary school and middle school students are the foremost consumers of these games. The addictive possibility of digital games has been revealed by the studies. It is known that digital game addiction can lead to loneliness as well as many problems. This study aimed to examine the studies in relation to the relationship between digital game addiction and loneliness in primary school and middle school students and to discuss the issue in general terms. As a result of the examination related to the issue, it has been concluded that primary and secondary school students who addicted to digital games have higher levels of loneliness.

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    İbn Haldun Çalışmaları Dergisi
    Article . 2023 . Peer-reviewed
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      İbn Haldun Çalışmaları Dergisi
      Article . 2023 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Ibrahim Mulushewa Eshete;

    In debates over the nature of the Ottoman social formation, most 20thcentury Turkish historians have tended to argue that it was “not feudal.” I argue that this is mostly because of the extent to which they have unconsciously imported and internalized Eurocentrism. In particular, it is because they have been using a Euro-specific notion or definition of feudalism as their yardstick. Also involved is a methodological, indeed philosophical failure to differentiate between genus and species, between the specific and the general. What is common to most agrarian states and societies in pre-modernity is the existence of a fief-system. But once a royal power-center resorts to fief-distribution, different power configurations can result. It is this revisionist approach to taxonomy that is proposed in this article, derived from my recently completed PhD thesis on civilizations’ common structures. Osmanlı toplumsal oluşumunun doğasına ilişkin tartışmalarda, 20. yüzyıl Türk tarihçilerinin çoğu bunun "feodal olmadığını" iddia etme eğilimindeydiler. Bunun Avrupa merkezciliğinin bilinçsizce ithal edilerek içselleştirmelerinden kaynaklandığını iddia edilmektedir. Bunun nedeni özellikle Avrupa'ya özgü bir feodalizm kavramını veya tanımını kıstas olarak kullanıyor olmalarıdır. Ayrıca cins ve tür arasında, özel ve genel arasında ayrım yapma konusundaki metodolojik, aslında felsefi bir başarısızlık da söz konusudur. Modernite öncesi tarım devletlerinin ve toplumlarının çoğunda ortak olan şey, bir tımar sisteminin varlığıdır. Ancak bir kraliyet güç merkezi, tımar dağıtımına başvurduğunda, farklı güç konfigürasyonları ortaya çıkabilir. Bu makalede önerilen, uygarlıkların ortak yapıları üzerine yakın zamanda tamamladığım doktora tezimden türetilen, taksonomiye yönelik bu revizyonist yaklaşımdır.

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    İbn Haldun Çalışmaları Dergisi
    Article . 2023 . Peer-reviewed
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      İbn Haldun Çalışmaları Dergisi
      Article . 2023 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Meng Zhang; Madhuri Sankaranarayanapillai; Jingcheng Du; Yang Xiang; +5 Authors

    Abstract Background With more clinical trials are offering optional participation in the collection of bio-specimens for biobanking comes the increasing complexity of requirements of informed consent forms. The aim of this study is to develop an automatic natural language processing (NLP) tool to annotate informed consent documents to promote biorepository data regulation, sharing, and decision support. We collected informed consent documents from several publicly available sources, then manually annotated them, covering sentences containing permission information about the sharing of either bio-specimens or donor data, or conducting genetic research or future research using bio-specimens or donor data. Results We evaluated a variety of machine learning algorithms including random forest (RF) and support vector machine (SVM) for the automatic identification of these sentences. 120 informed consent documents containing 29,204 sentences were annotated, of which 1250 sentences (4.28%) provide answers to a permission question. A support vector machine (SVM) model achieved a F-1 score of 0.95 on classifying the sentences when using a gold standard, which is a prefiltered corpus containing all relevant sentences. Conclusions This study provides the feasibility of using machine learning tools to classify permission-related sentences in informed consent documents.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ BMC Bioinformaticsarrow_drop_down
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    BMC Bioinformatics
    Article . 2023
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    BMC Bioinformatics
    Article . 2023 . Peer-reviewed
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ BMC Bioinformaticsarrow_drop_down
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      BMC Bioinformatics
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    Authors: Joel, Zirkle; Xiaomei, Han; Rebecca, Racz; Mohammadreza, Samieegohar; +4 Authors

    Abstract Background During drug development, it is essential to gather information about the change of clinical exposure of a drug (object) due to the pharmacokinetic (PK) drug-drug interactions (DDIs) with another drug (precipitant). While many natural language processing (NLP) methods for DDI have been published, most were designed to evaluate if (and what kind of) DDI relationships exist in the text, without identifying the direction of DDI (object vs. precipitant drug). Here we present a method for the automatic identification of the directionality of a PK DDI from literature or drug labels. Methods We reannotated the Text Analysis Conference (TAC) DDI track 2019 corpus for identifying the direction of a PK DDI and evaluated the performance of a fine-tuned BioBERT model on this task by following the training and validation steps prespecified by TAC. Results This initial attempt showed the model achieved an F-score of 0.82 in identifying sentences as containing PK DDI and an F-score of 0.97 in identifying object versus precipitant drugs in those sentences. Discussion and conclusion Despite a growing list of NLP methods for DDI extraction, most of them use a common set of corpora to perform general purpose tasks (e.g., classifying a sentence into one of several fixed DDI categories). There is a lack of coordination between the drug development and biomedical informatics method development community to develop corpora and methods to perform specific tasks (e.g., extract clinical exposure changes due to PK DDI). We hope that our effort can encourage such a coordination so that more “fit for purpose” NLP methods could be developed and used to facilitate the drug development process.

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    BMC Bioinformatics
    Article . 2023
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    BMC Bioinformatics
    Article . 2023 . Peer-reviewed
    License: CC BY
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      BMC Bioinformatics
      Article . 2023 . Peer-reviewed
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    Authors: Maryam Gholipour; Reza Khajouei; Parastoo Amiri; Sadrieh Hajesmaeel Gohari; +1 Authors

    Abstract Background Extracting information from free texts using natural language processing (NLP) can save time and reduce the hassle of manually extracting large quantities of data from incredibly complex clinical notes of cancer patients. This study aimed to systematically review studies that used NLP methods to identify cancer concepts from clinical notes automatically. Methods PubMed, Scopus, Web of Science, and Embase were searched for English language papers using a combination of the terms concerning “Cancer”, “NLP”, “Coding”, and “Registries” until June 29, 2021. Two reviewers independently assessed the eligibility of papers for inclusion in the review. Results Most of the software programs used for concept extraction reported were developed by the researchers (n = 7). Rule-based algorithms were the most frequently used algorithms for developing these programs. In most articles, the criteria of accuracy (n = 14) and sensitivity (n = 12) were used to evaluate the algorithms. In addition, Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT) and Unified Medical Language System (UMLS) were the most commonly used terminologies to identify concepts. Most studies focused on breast cancer (n = 4, 19%) and lung cancer (n = 4, 19%). Conclusion The use of NLP for extracting the concepts and symptoms of cancer has increased in recent years. The rule-based algorithms are well-liked algorithms by developers. Due to these algorithms' high accuracy and sensitivity in identifying and extracting cancer concepts, we suggested that future studies use these algorithms to extract the concepts of other diseases as well.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ BMC Bioinformaticsarrow_drop_down
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    BMC Bioinformatics
    Article . 2023
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    BMC Bioinformatics
    Article . 2023 . Peer-reviewed
    License: CC BY
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      BMC Bioinformatics
      Article . 2023 . Peer-reviewed
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    Authors: Haitham A, Elmarakeby; Pavel S, Trukhanov; Vidal M, Arroyo; Irbaz Bin, Riaz; +3 Authors

    Abstract Background Longitudinal data on key cancer outcomes for clinical research, such as response to treatment and disease progression, are not captured in standard cancer registry reporting. Manual extraction of such outcomes from unstructured electronic health records is a slow, resource-intensive process. Natural language processing (NLP) methods can accelerate outcome annotation, but they require substantial labeled data. Transfer learning based on language modeling, particularly using the Transformer architecture, has achieved improvements in NLP performance. However, there has been no systematic evaluation of NLP model training strategies on the extraction of cancer outcomes from unstructured text. Results We evaluated the performance of nine NLP models at the two tasks of identifying cancer response and cancer progression within imaging reports at a single academic center among patients with non-small cell lung cancer. We trained the classification models under different conditions, including training sample size, classification architecture, and language model pre-training. The training involved a labeled dataset of 14,218 imaging reports for 1112 patients with lung cancer. A subset of models was based on a pre-trained language model, DFCI-ImagingBERT, created by further pre-training a BERT-based model using an unlabeled dataset of 662,579 reports from 27,483 patients with cancer from our center. A classifier based on our DFCI-ImagingBERT, trained on more than 200 patients, achieved the best results in most experiments; however, these results were marginally better than simpler “bag of words” or convolutional neural network models. Conclusion When developing AI models to extract outcomes from imaging reports for clinical cancer research, if computational resources are plentiful but labeled training data are limited, large language models can be used for zero- or few-shot learning to achieve reasonable performance. When computational resources are more limited but labeled training data are readily available, even simple machine learning architectures can achieve good performance for such tasks.

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    BMC Bioinformatics
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      BMC Bioinformatics
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    Authors: Nikitha Karkera; Sathwik Acharya; Sucheendra K. Palaniappan;

    Abstract Background The growing recognition of the microbiome’s impact on human health and well-being has prompted extensive research into discovering the links between microbiome dysbiosis and disease (healthy) states. However, this valuable information is scattered in unstructured form within biomedical literature. The structured extraction and qualification of microbe-disease interactions are important. In parallel, recent advancements in deep-learning-based natural language processing algorithms have revolutionized language-related tasks such as ours. This study aims to leverage state-of-the-art deep-learning language models to extract microbe-disease relationships from biomedical literature. Results In this study, we first evaluate multiple pre-trained large language models within a zero-shot or few-shot learning context. In this setting, the models performed poorly out of the box, emphasizing the need for domain-specific fine-tuning of these language models. Subsequently, we fine-tune multiple language models (specifically, GPT-3, BioGPT, BioMedLM, BERT, BioMegatron, PubMedBERT, BioClinicalBERT, and BioLinkBERT) using labeled training data and evaluate their performance. Our experimental results demonstrate the state-of-the-art performance of these fine-tuned models ( specifically GPT-3, BioMedLM, and BioLinkBERT), achieving an average F1 score, precision, and recall of over $$>0.8$$ > 0.8 compared to the previous best of 0.74. Conclusion Overall, this study establishes that pre-trained language models excel as transfer learners when fine-tuned with domain and problem-specific data, enabling them to achieve state-of-the-art results even with limited training data for extracting microbiome-disease interactions from scientific publications.

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    BMC Bioinformatics
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    Authors: Muhammet İkbal Bakır;

    Bu makale Hegel felsefesini temel alarak özne kavramını ele almaya çalışıyor. Genel olarak Hegel’in bize önerdiği özneyi, klasik felsefedeki özne kavrayışından oldukça farklı bir yerde buluyor. Bu yeni kavrayış, özneyi bir sabitlik ve kendine eşitlik olarak düşünmüyor; bunun yerine özneyi sürekli kendine dönen bir hareket olarak düşünüyor. Öznenin bir hareket olarak düşünülmesini ise daha çok çatallanma ve dolayım kavramlarından itibaren anlamaya çalışıyor. Bundan başka; bu makale, Hegelci özne yapısı içinde kalarak Hegelci özneyi eleştirmeye çalışıyor ve onun ötesinde bir özne kavrayışı sunmaya çalışıyor. Bu eleştiri ve önerinin temel kavramlarını ise ‘ayrık özne’, ‘gömülü özne’, ruh ve insan kavramları teşkil ediyor. This article tries to deal with the concept of the subject based on Hegel's philosophy. In general, Hegel's conception of the subject is quite different from the conception of the subject in classical philosophy. This new conception does not think of the subject as a fixity and equality to itself; instead, it thinks of the subject as a movement that constantly returns to itself. He tries to understand the conception of the subject as a movement from the concepts of bifurcation and mediation. Furthermore, this article tries to criticize the Hegelian subject by staying within the Hegelian subject structure and tries to offer a conception of the subject beyond it. The basic concepts of this critique and proposal are the concepts of 'cynical subject', 'embedded subject', soul and human being.

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    Authors: Mevlan Tanrıkut;

    The Reign of Xi Jinping has been characterized as assertive, unapologetic, and autocratic both at home and abroad(So, 2019). His strict control over Chinese companies and cracking down on private high-tech companies have become debated. If we look back economic system of the Chinese Communist Party, we will find that state control of the economy has been the primary trend. One might ask, what are the reasons for the Chinese Communist Party, particularly Xi Jinping’s sensitiveness to private business, and where has the idea of state monopoly over the private sector originated? By highlighting the importance of the historical approach, rather than a progressive one, for analyzing the statecraft in contemporary China methodologically, the present paper tries to address this question by examiningthe Discourses on Salt and Iron, a famous classic piece recorded by Huan Kuan of the Han Dynasty (202 BC –220 AD) and its legacy in successive governments. The first part of the paper focuses on the historical background of the Chinese state monopoly, which aims to show the historical event that led to the implementation of monopolistic economic policies and supportive rational arguments for its continuation. The second part sheds light on the continuation of this policy and illustrates howand why this policy is still alive today. By pondering above all, this study argues that China’s main concern in the economy is maintaining the power gap between the authority and private merchants, which is the legacy of traditional Chinese statecraft. Xi Jinping yönetimi, ulusal ve uluslararası düzeyde iddialı, özür dilemeyen ve otokratik olarak nitelendirilmektedir. Çinli şirketler üzerindeki sıkı kontrol ve yüksek teknoloji şirketlerine yönelik baskılar geniş çapta tartışmalara konu olmaktadır. Çin Komünist Partisi'nin ekonomik sistemine bakıldığında da, devlet kontrolünün temel bir eğilim olduğu görülmektedir. Xi'in özel sektöre olan hassasiyetinin nedeni ve özel sektör üzerinde devlet tekeli fikri, sorulabilecek önemli sorulardır. Bu makale, Çağdaş Çin'deki devlet yönetimini ilerici bir metodoloji yerine tarihsel bir yaklaşımla inceleyerek, Tuz ve Demir Üzerine Söylevler adlı ünlü klasik eserin ana fikiri ve onun ardışık hükümetlerdeki mirasını analiz ederek bu sorulara cevap aramaktadır. İlk bölüm tarihsel bir perspektifle, tekelci ekonomi politikalarının tarihsel arka planı bu politikayı destekleyici rasyonel argümanları göstermeyi odaklanmaktadır. İkinci bölüm ise bu politikanın günümüzde nasıl ve neden hala canlı olduğunu açıklamaya çalışmaktadır. Bunları analız derek bu çalışma, Çin'in ekonomideki ana endişesinin, geleneksel Çin devlet yönetiminin mirası olan otorite ile özel sektör arasındaki güç farkını korumak olduğunu savunmaktadır.

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    Authors: Mohammad Javid Fedayee;

    This article is a study of the social and political works of Ibn Khaldun, a famous 14th-century Muslim historian, philosopher, and scholar. His insights into the field of social dynamics of international relations were widely acclaimed and still influence current scholars. Ibn Khaldun's methodof history was distinctive, which is emphasizing how social institutions and human behavior shaped historical facts. The Muqqddima, his seminal work, offered a thorough examination of the cycles and patterns of human behavior and the evolution of society,especially in the area of international relations. Ibn Khaldun's Asabiya, Umran, Rural and Urban life, State, and Power are his most fascinating works, and his Umran can be considered a universal civilization. His concepts still help us understand the complexity of human behavior and social development, especially in international relations. Bu makale, 14. yüzyılda yaşamış ünlü Müslüman tarihçi, filozof ve akademisyen İbn Haldun'un sosyal ve siyasi eserleri üzerine bir çalışmadır. Uluslararası ilişkilerin sosyal dinamikleri alanındaki görüşleri büyük beğeni toplamış ve günümüz akademisyenlerini hala etkilemektedir. İbn Haldun'un tarih metodu, sosyal kurumların ve insan davranışlarının tarihsel olguları nasıl şekillendirdiğini vurgulayan kendine özgü bir metottur. İbn Haldun'un ufuk açıcı eseri Mukaddime, özellikle uluslararası ilişkiler alanında insan davranışının döngüleri ve kalıpları ile toplumun evriminin kapsamlı bir incelemesini sunmuştur. İbn Haldun'un Asabiye, Umran, kırsal ve kentsel yaşam, devlet ve iktidar en etkileyici eserleridir ve Umran'ı evrensel bir medeniyet olarak kabul edilebilir. Onun kavramları, özellikle uluslararası ilişkilerde insan davranışının ve sosyal gelişimin karmaşıklığını anlamamıza hala yardımcı olmaktadır.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ İbn Haldun Çalışmala...arrow_drop_down
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    İbn Haldun Çalışmaları Dergisi
    Article . 2023 . Peer-reviewed
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ İbn Haldun Çalışmala...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      İbn Haldun Çalışmaları Dergisi
      Article . 2023 . Peer-reviewed
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Authors: Ekrem Erden; Sefa Bulut;

    Son yıllarda yaşanan teknolojik gelişmeler, teknolojik cihazların artan üretimi ve yaygınlaşması, dijital cihazlara erişimi kolaylaştırmıştır. Artık günlük yaşamın birçok alanında vazgeçilmez haline gelen dijital araçların eğlence alanında da aynı konuma geldiği söylenebilir. Dijital oyunlar günümüzde yaygın bir şekilde her yaş grubundaki insan tarafından oynanmaktadır. Ancak ilkokul ve ortaokul çağındaki öğrenciler bu oyunların ilk sırada gelen tüketicileri arasındadır. Dijital oyunların bağımlılık yapma potansiyeli ise yapılan çalışmalar tarafından ortaya konulmuştur. Dijital oyun bağımlılığının, birçok problemin yanında yalnızlığa yol açabileceği bilinmektedir. Bu çalışma, ilkokul ve ortaokul öğrencilerinin dijital oyun bağımlılıkları ve yalnızlık arasındaki ilişki ile ilgili yapılan çalışmaları incelemek ve konuyu genel hatlarıyla tartışmak amacıyla yapılmıştır. Dijital oyun bağımlılığının tanımı ve kriterleri, etiyolojisi, kız ve erkek öğrenciler arasındaki farklılıklar, yalnızlık, koruyucu faktörler verisk faktörleri güncel araştırmalar ışığında tartışılmış ve ailelere öneriler sunulmuştur. Konuyla ilgili araştırmaların incelenmesi sonucunda dijital oyun bağımlısı olan ilkokul ve ortaokul öğrencilerinin yalnızlık düzeylerinin daha yüksek olduğu sonucuna ulaşılmıştır. Technological developments in recent years, increased production, and the proliferation of technological devices have facilitated to reach digital devices. It is possible to say that digital devices that have become indispensable in many areas of daily life have attained the same location in the entertainment field. Digital games are widely played by people of all age groups today, but primary school and middle school students are the foremost consumers of these games. The addictive possibility of digital games has been revealed by the studies. It is known that digital game addiction can lead to loneliness as well as many problems. This study aimed to examine the studies in relation to the relationship between digital game addiction and loneliness in primary school and middle school students and to discuss the issue in general terms. As a result of the examination related to the issue, it has been concluded that primary and secondary school students who addicted to digital games have higher levels of loneliness.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ İbn Haldun Çalışmala...arrow_drop_down
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    İbn Haldun Çalışmaları Dergisi
    Article . 2023 . Peer-reviewed
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      İbn Haldun Çalışmaları Dergisi
      Article . 2023 . Peer-reviewed
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Authors: Ibrahim Mulushewa Eshete;

    In debates over the nature of the Ottoman social formation, most 20thcentury Turkish historians have tended to argue that it was “not feudal.” I argue that this is mostly because of the extent to which they have unconsciously imported and internalized Eurocentrism. In particular, it is because they have been using a Euro-specific notion or definition of feudalism as their yardstick. Also involved is a methodological, indeed philosophical failure to differentiate between genus and species, between the specific and the general. What is common to most agrarian states and societies in pre-modernity is the existence of a fief-system. But once a royal power-center resorts to fief-distribution, different power configurations can result. It is this revisionist approach to taxonomy that is proposed in this article, derived from my recently completed PhD thesis on civilizations’ common structures. Osmanlı toplumsal oluşumunun doğasına ilişkin tartışmalarda, 20. yüzyıl Türk tarihçilerinin çoğu bunun "feodal olmadığını" iddia etme eğilimindeydiler. Bunun Avrupa merkezciliğinin bilinçsizce ithal edilerek içselleştirmelerinden kaynaklandığını iddia edilmektedir. Bunun nedeni özellikle Avrupa'ya özgü bir feodalizm kavramını veya tanımını kıstas olarak kullanıyor olmalarıdır. Ayrıca cins ve tür arasında, özel ve genel arasında ayrım yapma konusundaki metodolojik, aslında felsefi bir başarısızlık da söz konusudur. Modernite öncesi tarım devletlerinin ve toplumlarının çoğunda ortak olan şey, bir tımar sisteminin varlığıdır. Ancak bir kraliyet güç merkezi, tımar dağıtımına başvurduğunda, farklı güç konfigürasyonları ortaya çıkabilir. Bu makalede önerilen, uygarlıkların ortak yapıları üzerine yakın zamanda tamamladığım doktora tezimden türetilen, taksonomiye yönelik bu revizyonist yaklaşımdır.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Ibn Haldun Universit...arrow_drop_down
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    İbn Haldun Çalışmaları Dergisi
    Article . 2023 . Peer-reviewed
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