Objective To discover candidate drugs to repurpose for COVID-19 using literature-derived
knowledge and knowledge graph completion methods. Methods We propose a novel …

The cost of drug development continues to rise and may be prohibitive in cases of unmet
clinical need, particularly for rare diseases. Artificial intelligence-based methods are …

Natural language processing (NLP) is an area of artificial intelligence that applies
information technologies to process the human language, understand it to a certain degree …

In this paper, we present Knowledge4COVID-19, a framework that aims to showcase the
power of integrating disparate sources of knowledge to discover adverse drug effects …

Background Many important clinical decisions require causal knowledge (CK) to take action.
Although many causal knowledge bases for medicine have been constructed, a …

Abstract PubTator 3.0 (https://www. ncbi. nlm. nih. gov/research/pubtator3/) is a biomedical
literature resource using state-of-the-art AI techniques to offer semantic and relation …

OpCitance contains all the sentences from 2 million PubMed Central open-access (PMCOA)
articles, with 137 million inline citations annotated (ie, the “citation contexts”). Parsing out the …

There are over 6,000 different rare diseases estimated to impact 300 million people
worldwide. As genetic testing becomes more common practice in the clinical setting, the …

Background Computational drug repurposing is a cost-and time-efficient approach that aims
to identify new therapeutic targets or diseases (indications) of existing drugs/compounds. It …

Efficient remote monitoring of the patient infected with coronavirus without spread to
healthcare workers is the need of the hour. An effectual and faster communication system …