With the widespread adoption of electronic health records (EHRs), large repositories of
structured and unstructured patient data are becoming available to conduct observational …

With the completion of the Human Genome Project1 as well as recent advances in genomic
science and comparative biological studies, a new era of individualized medicine is evolving …

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 …

Today, healthcare has become one of the largest and most fast‐paced industries due to the
rapid development of digital healthcare technologies. The fundamental thing to enhance …

A review of published work in clinical natural language processing (NLP) may suggest that
the negation detection task has been “solved.” This work proposes that an optimizable …

Data from the electronic medical record comprise numerous structured but uncoded ele-
ments, which are not linked to standard terminologies. Reuse of such data for secondary …

Cancer registries collect unstructured and structured cancer data for surveillance purposes
which provide important insights regarding cancer characteristics, treatments, and …

Quality annotated resources are essential for Natural Language Processing. The objective
of this work is to present a corpus of clinical narratives in French annotated for linguistic …

Non-used clinical information has negative implications on healthcare quality. Clinicians pay
priority attention to clinical information relevant to their specialties during routine clinical …

Background Observational clinical studies play a pivotal role in advancing medical
knowledge and patient healthcare. To lessen the prohibitive costs of conducting these …