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  • Digital Humanities and Cultural Heritage
  • National Institutes of Health

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  • Authors: Cejuela, Juan Miguel; Campos, Jorge; tagtog;

    Automatic, manual, and search annotation tool.

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    Authors: Xinhang, Li; Hao, Liu; Fabrício, Kury; Chi, Yuan; +5 Authors

    Human annotations are the established gold standard for evaluating natural language processing (NLP) methods. The goals of this study are to quantify and qualify the disagreement between human and NLP. We developed an NLP system for annotating clinical trial eligibility criteria text and constructed a manually annotated corpus, both following the OMOP Common Data Model (CDM). We analyzed the discrepancies between the human and NLP annotations and their causes (e.g., ambiguities in concept categorization and tacit decisions on inclusion of qualifiers and temporal attributes during concept annotation). This study initially reported complexities in clinical trial eligibility criteria text that complicate NLP and the limitations of the OMOP CDM. The disagreement between and human and NLP annotations may be generalizable. We discuss implications for NLP evaluation.

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    Europe PubMed Central
    Other literature type . 2021
    Data sources: PubMed Central
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      Europe PubMed Central
      Other literature type . 2021
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    Authors: Huan, He; Sunyang, Fu; Liwei, Wang; Andrew, Wen; +4 Authors

    A gold standard annotated corpus is usually indispensable when developing natural language processing (NLP) systems. Building a high-quality annotated corpus for clinical NLP requires considerable time and domain expertise during the annotation process. Existing annotation tools may provide powerful features to cover various needs of text annotation tasks, but the target end users tend to be trained annotators. It is challenging for clinical research teams to utilize those tools in their projects due to various factors such as the complexity of advanced features and data security concerns. To address those challenges, we developed MedTator, a serverless web-based annotation tool with an intuitive user-centered interface aiming to provide a lightweight solution for the core tasks in corpus development. Moreover, we present three lessons learned from the designing and developing MedTator, which will contribute to the research community’s knowledge for future open-source tool development.

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    Europe PubMed Central
    Other literature type . 2023
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      Europe PubMed Central
      Other literature type . 2023
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    Authors: Wu, Canglin;

    Restructured version of Gene Expression Omnibus (GEO) that provides a user friendly interface for curating GEO database

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    bio.tools
    Software . 2019
    Data sources: bio.tools
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      bio.tools
      Software . 2019
      Data sources: bio.tools
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    Authors: Davis, Sean;

    Package that facilitates access to extensive metadata in computable form covering the Bioconductor package ecosystem, facilitating downstream applications such as custom reporting, data and text mining of Bioconductor package text descriptions, graph analytics over package dependencies, and custom search approaches.

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    bio.tools
    Software . 2019
    License: MIT
    Data sources: bio.tools
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      bio.tools
      Software . 2019
      License: MIT
      Data sources: bio.tools
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    Authors: Douglas Redd; Terri Elizabeth Workman; Yijun Shao; Yan Cheng; +4 Authors

    There is widespread use of dietary supplements, some prescribed but many taken without a physician’s guidance. There are many potential interactions between supplements and both over-the-counter and prescription medications in ways that are unknown to patients. Structured medical records do not adequately document supplement use; however, unstructured clinical notes often contain extra information on supplements. We studied a group of 377 patients from three healthcare facilities and developed a natural language processing (NLP) tool to detect supplement use. Using surveys of these patients, we investigated the correlation between self-reported supplement use and NLP extractions from the clinical notes. Our model achieved an F1 score of 0.914 for detecting all supplements. Individual supplement detection had a variable correlation with survey responses, ranging from an F1 of 0.83 for calcium to an F1 of 0.39 for folic acid. Our study demonstrated good NLP performance while also finding that self-reported supplement use is not always consistent with the documented use in clinical records.

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    Medical Sciences
    Other literature type . Article . 2023 . Peer-reviewed
    License: CC BY
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    Medical Sciences
    Article . 2023
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      Medical Sciences
      Other literature type . Article . 2023 . Peer-reviewed
      License: CC BY
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      Medical Sciences
      Article . 2023
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    Authors: Jensen, Lars Juhl; Gorodkin, Jan;

    TISSUES is a weekly updated web resource that integrates evidence on tissue expression from manually curated literature, proteomics and transcriptomics screens, and automatic text mining. We map all evidence to common protein identifiers and Brenda Tissue Ontology terms, and further unify it by assigning confidence scores that facilitate comparison of the different types and sources of evidence. We finally visualize these scores on a schematic human body to provide a convenient overview.

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    bio.tools
    Software . 2018
    License: CC-BY-4.0
    Data sources: bio.tools
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      bio.tools
      Software . 2018
      License: CC-BY-4.0
      Data sources: bio.tools
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    Authors: Wang, Kai; Weng, Chunhua;

    Web application for efficient and accurate Human Phenotype Ontology (HPO) concept curation.

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    bio.tools
    Software . 2019
    License: Unlicense
    Data sources: bio.tools
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      bio.tools
      Software . 2019
      License: Unlicense
      Data sources: bio.tools
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    Authors: Alex S Cohen; Zachary Rodriguez; Kiara K Warren; Tovah Cowan; +6 Authors

    Abstract Background and Hypothesis Despite decades of “proof of concept” findings supporting the use of Natural Language Processing (NLP) in psychosis research, clinical implementation has been slow. One obstacle reflects the lack of comprehensive psychometric evaluation of these measures. There is overwhelming evidence that criterion and content validity can be achieved for many purposes, particularly using machine learning procedures. However, there has been very little evaluation of test-retest reliability, divergent validity (sufficient to address concerns of a “generalized deficit”), and potential biases from demographics and other individual differences. Study Design This article highlights these concerns in development of an NLP measure for tracking clinically rated paranoia from video “selfies” recorded from smartphone devices. Patients with schizophrenia or bipolar disorder were recruited and tracked over a week-long epoch. A small NLP-based feature set from 499 language samples were modeled on clinically rated paranoia using regularized regression. Study Results While test–retest reliability was high, criterion, and convergent/divergent validity were only achieved when considering moderating variables, notably whether a patient was away from home, around strangers, or alone at the time of the recording. Moreover, there were systematic racial and sex biases in the model, in part, reflecting whether patients submitted videos when they were away from home, around strangers, or alone. Conclusions Advancing NLP measures for psychosis will require deliberate consideration of test-retest reliability, divergent validity, systematic biases and the potential role of moderators. In our example, a comprehensive psychometric evaluation revealed clear strengths and weaknesses that can be systematically addressed in future research.

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    Europe PubMed Central
    Other literature type . 2022
    Data sources: PubMed Central
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    Schizophrenia Bulletin
    Article . 2022 . Peer-reviewed
    License: OUP Standard Publication Reuse
    Data sources: Crossref
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      Europe PubMed Central
      Other literature type . 2022
      Data sources: PubMed Central
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      Schizophrenia Bulletin
      Article . 2022 . Peer-reviewed
      License: OUP Standard Publication Reuse
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  • Authors: Kwok, Elaine Yuen Ling; Feiner, Hannah; Grauzer, Jeffrey; Kaat, Aaron J.; +1 Authors

    Purpose: Norm-referenced, standardized measures are tools designed to characterize a child’s abilities relative to their same-age peers, but they also have been used to measure changes in skills during intervention. This study compared the psychometric properties of four types of available scores from one commonly used standardized measure, the Preschool Language Scales–Fifth Edition (PLS-5), to detect changes in children’s language skills during and after a language intervention. Method: This study included data from 110 autistic children aged 18–48 months whose mother participated in an 8-week parent-mediated language intervention. Children’s language skills were measured at 3 time points using the PLS-5. Changes in children’s expressive and receptive language skills were calculated using raw scores, standard scores, age equivalents, and growth scale values (GSVs). Results: Analysis of raw scores, age equivalents, and GSVs indicated significant improvement in the scores of autistic children in both receptive and expressive language throughout the study (i.e., during the intervention period and in the 3-month period after the intervention). Standard scores suggested improvement only in the receptive language scale during the intervention period. Standard scores showed a floor effect for children who scored at −3 SD below the mean. Conclusions: Findings suggested that GSVs were not only psychometrically sound but also the most sensitive measure of direct changes in skills compared to raw, standard, and age-equivalent scores. Floor effects may limit the sensitivity of standard scores to detect changes in children’s skills. Strengths, limitations, and interpretations of each of the scoring approaches in measuring changes in skills during intervention were discussed. Supplemental Material S1. Effect size of changes from intervention as measured by each scoring approaches (with nonparametric Wilcoxon signed-rank test). Kwok, E., Feiner, H., Grauzer, J., Kaat, A., & Roberts, M. Y. (2022). Measuring change during intervention using norm-referenced, standardized measures: A comparison of raw scores, standard scores, age equivalents, and growth scale values from the Preschool Language Scales–Fifth Edition. Journal of Speech, Language, and Hearing Research. Advance online publication. https://doi.org/10.1044/2022_JSLHR-22-00122

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  • Authors: Cejuela, Juan Miguel; Campos, Jorge; tagtog;

    Automatic, manual, and search annotation tool.

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    Authors: Xinhang, Li; Hao, Liu; Fabrício, Kury; Chi, Yuan; +5 Authors

    Human annotations are the established gold standard for evaluating natural language processing (NLP) methods. The goals of this study are to quantify and qualify the disagreement between human and NLP. We developed an NLP system for annotating clinical trial eligibility criteria text and constructed a manually annotated corpus, both following the OMOP Common Data Model (CDM). We analyzed the discrepancies between the human and NLP annotations and their causes (e.g., ambiguities in concept categorization and tacit decisions on inclusion of qualifiers and temporal attributes during concept annotation). This study initially reported complexities in clinical trial eligibility criteria text that complicate NLP and the limitations of the OMOP CDM. The disagreement between and human and NLP annotations may be generalizable. We discuss implications for NLP evaluation.

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    Europe PubMed Central
    Other literature type . 2021
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      Europe PubMed Central
      Other literature type . 2021
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    Authors: Huan, He; Sunyang, Fu; Liwei, Wang; Andrew, Wen; +4 Authors

    A gold standard annotated corpus is usually indispensable when developing natural language processing (NLP) systems. Building a high-quality annotated corpus for clinical NLP requires considerable time and domain expertise during the annotation process. Existing annotation tools may provide powerful features to cover various needs of text annotation tasks, but the target end users tend to be trained annotators. It is challenging for clinical research teams to utilize those tools in their projects due to various factors such as the complexity of advanced features and data security concerns. To address those challenges, we developed MedTator, a serverless web-based annotation tool with an intuitive user-centered interface aiming to provide a lightweight solution for the core tasks in corpus development. Moreover, we present three lessons learned from the designing and developing MedTator, which will contribute to the research community’s knowledge for future open-source tool development.

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    Europe PubMed Central
    Other literature type . 2023
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      Europe PubMed Central
      Other literature type . 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/
    Authors: Wu, Canglin;

    Restructured version of Gene Expression Omnibus (GEO) that provides a user friendly interface for curating GEO database

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    bio.tools
    Software . 2019
    Data sources: bio.tools
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      bio.tools
      Software . 2019
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    Authors: Davis, Sean;

    Package that facilitates access to extensive metadata in computable form covering the Bioconductor package ecosystem, facilitating downstream applications such as custom reporting, data and text mining of Bioconductor package text descriptions, graph analytics over package dependencies, and custom search approaches.

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    bio.tools
    Software . 2019
    License: MIT
    Data sources: bio.tools
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      bio.tools
      Software . 2019
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    Authors: Douglas Redd; Terri Elizabeth Workman; Yijun Shao; Yan Cheng; +4 Authors

    There is widespread use of dietary supplements, some prescribed but many taken without a physician’s guidance. There are many potential interactions between supplements and both over-the-counter and prescription medications in ways that are unknown to patients. Structured medical records do not adequately document supplement use; however, unstructured clinical notes often contain extra information on supplements. We studied a group of 377 patients from three healthcare facilities and developed a natural language processing (NLP) tool to detect supplement use. Using surveys of these patients, we investigated the correlation between self-reported supplement use and NLP extractions from the clinical notes. Our model achieved an F1 score of 0.914 for detecting all supplements. Individual supplement detection had a variable correlation with survey responses, ranging from an F1 of 0.83 for calcium to an F1 of 0.39 for folic acid. Our study demonstrated good NLP performance while also finding that self-reported supplement use is not always consistent with the documented use in clinical records.

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    Medical Sciences
    Other literature type . Article . 2023 . Peer-reviewed
    License: CC BY
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    Medical Sciences
    Article . 2023
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      Other literature type . Article . 2023 . Peer-reviewed
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      Medical Sciences
      Article . 2023
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