Objectives We examine recent published research on the extraction of information from
textual documents in the Electronic Health Record (EHR). Methods Literature review of the …

The UMLS Metathesaurus, the largest thesaurus in the biomedical domain, provides a
representation of biomedical knowledge consisting of concepts classified by semantic type …

Objective: The aim of this study was to develop a method based on natural language
processing (NLP) that automatically maps an entire clinical document to codes with …

Objectives To provide typical examples of biomedical ontologies in action, emphasizing the
role played by biomedical ontologies in knowledge management, data integration and …

Randomized controlled trials (RCTs) are one of the least biased sources of clinical research
evidence, and are therefore a critical resource for the practice of evidence-based medicine …

Medical Informatics and biomedical computing have grown in quantum measure over the
past decade. An abundance of advances have come to the foreground in this field with the …

Objective: To develop methods that automatically map abbreviations to their full forms in
biomedical articles. Methods: The authors developed two methods of map** defined and …

Background The medical problem list is an important part of the electronic medical record in
development in our institution. To serve the functions it is designed for, the problem list has …

MediClass is a knowledge-based system that processes both free-text and coded data to
automatically detect clinical events in electronic medical records (EMRs). This technology …

Extracting key concepts from clinical texts for indexing is an important task in implementing a
medical digital library. Several methods are proposed for map** free text into standard …