Abstract With the increase in volume of data and presence of structured and unstructured data in the biomedical filed, there is a need for building models which can handle complex & non-linear relations in the data and also predict and classify outcomes with higher ...

AbstractNeuroscience has become increasingly reliant on multi-subject research in addition to studies of unusual single patients. This research has brought with it a challenge: how are data from di...

In this work, we formulated the named entity recognition (NER) task as a multi-answer knowledge guided question-answer task (KGQA) and showed that the knowledge guidance helps to achieve state-of-the-art results for 11 of 18 biomedical NER datasets. We prepended five d...

Temporal knowledge base exists on various fields. Take medical medicine field as example, diabetes is a typical chronic disease which evolves slowly. This paper starts from actual EMR data of hospitals by combination of experience and knowledge of clinical doctors. Link...

Throughout the Negev Desert highlands, thousands of ancient petroglyphs sites are susceptible to deterioration processes that may result in the loss of this unique rock art. Therefore, the overarching goal of the current study was to characterize the composition, divers...

One curious phenomenon of several social groups is that they are ‘redundant’ in the sense that they contain more cooperators than strictly needed to complete certain group tasks, such as foraging. Redundancy is puzzling because redundant groups are particularly suscepti...

In this article, we present a thorough evaluation of semantic password grammars. We report multifactorial experiments that test the impact of sample size, probability smoothing, and linguistic information on password cracking. The semantic grammars are compared with st...

The origins of the calamitous SARS-CoV-2 pandemic are now the subject of vigorous discussion and debate between two competing hypotheses for how it entered the human population: (i) direct infection from a feral source, likely a bat and possibly with an intermediate mam...

As the COVID-19 pandemic continues to spread worldwide, an unprecedented amount of open data is being generated for medical, genetics, and epidemiological research. The unparalleled rate at which many research groups around the world are releasing data and publications ...

We study the task of recognizing named datasets in scientific articles as a Named Entity Recognition (NER) problem. Noticing that available annotated datasets were not adequate for our goals, we annotated 6000 sentences extracted from four major AI conferences, with rou...