Background With the rapid adoption of electronic health records (EHRs), it is desirable to
harvest information and knowledge from EHRs to support automated systems at the point of …

Electronic health records (EHRs), digital collections of patient healthcare events and
observations, are ubiquitous in medicine and critical to healthcare delivery, operations, and …

We followed a systematic approach based on the Preferred Reporting Items for Systematic
Reviews and Meta-Analyses to identify existing clinical natural language processing (NLP) …

Traditional approaches to the prediction of suicide attempts have limited the accuracy and
scale of risk detection for these dangerous behaviors. We sought to overcome these …

Existing general clinical natural language processing (NLP) systems such as MetaMap and
Clinical Text Analysis and Knowledge Extraction System have been successfully applied to …

Background The discovery of novel anticancer drugs is critical for the pharmaceutical
research and development, and patient treatment. Repurposing existing drugs that may …

Abstract Background Electronic medical records (EMRs) are revolutionizing health-related
research. One key issue for study quality is the accurate identification of patients with the …

Clinical data describing the phenotypes and treatment of patients represents an underused
data source that has much greater research potential than is currently realized. Mining of …

Sequence labeling for extraction of medical events and their attributes from unstructured text
in Electronic Health Record (EHR) notes is a key step towards semantic understanding of …

Drug‐induced liver injury (DILI) is the most frequent reason cited for the withdrawal of
approved drugs from the market and accounts for up to 15% of the cases of acute liver …