Work

Corpus-Based Problem Selection for EHR Note Summarization.

Year: 2010

Type: article

Abstract: Physicians have access to patient notes in volumes far greater than what is practical to read within the context of a standard clinical scenario. As a preliminary step toward being able to provide a longitudinal summary of patient history, methods are examined for the automated extraction of relevant patient problems from existing clinical notes. We explore a grounded approach to identifying important patient problems from patient history. Methods build on existing NLP and text-summarization methodologies and leverage features observed in a relevant corpus.

Source: PubMed Central

Authors: Tielman T Van Vleck, Noémie Elhadad

Institution: Columbia University

Language: English

Topic: Biomedical Text Mining and Ontologies

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

Open Access status: green

Funder: U.S. National Library of Medicine

Awards: Capturing and linking genomic and clinical information, A Biomedical Natural Language Processing Resource, Training in Biomedical Informatics at Columbia University, An NLP Approach to Generating Patient Record Summaries

OpenAlex ID: W75439561

FWCI: 0.457

Cites: 13

Cited by: 21

Related to: 10