The importance of incorporating Natural Language Processing (NLP) methods in clinical
informatics research has been increasingly recognized over the past years, and has led to …

Background Natural language processing applied to clinical text or aimed at a clinical
outcome has been thriving in recent years. This paper offers the first broad overview of …

Retrospectively collected medical data has the opportunity to improve patient care through
knowledge discovery and algorithm development. Broad reuse of medical data is desirable …

Clinical notes contain information about patients that goes beyond structured data like lab
values and medications. However, clinical notes have been underused relative to structured …

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

The CoNLL-2012 shared task involved predicting coreference in English, Chinese, and
Arabic, using the final version, v5. 0, of the OntoNotes corpus. It was a follow-on to the …

Background Concept extraction, a subdomain of natural language processing (NLP) with a
focus on extracting concepts of interest, has been adopted to computationally extract clinical …

Objectives We sought to use natural language processing to develop a suite of language
models to capture key symptoms of severe mental illness (SMI) from clinical text, to facilitate …

An important goal of the health system is to identify new adverse drug events (ADEs) in the
postapproval period. Data‐mining methods that can transform data into meaningful …

In this study we present novel feature engineering techniques that leverage the biomedical
domain knowledge encoded in the Unified Medical Language System (UMLS) to improve …