Extracting diagnoses from discharge summaries.

Extracting diagnoses from discharge summaries. Research Abstract Details 

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Extracting diagnoses from discharge summaries. Abstract Text:

William Long,

We have developed a program for extracting the diagnoses and procedures from the past medical history and discharge diagnoses in the discharge summary of a case and coding these using SNOMED-CT in the UMLS. The program uses a limited amount of natural language processing. Rather, it makes use of the relatively standard structure of the discharge summary, a small dictionary to divide the text into phrases, and the extensive collection of phrases for concepts in the UMLS to do the coding. With this approach the program finds 240 of 250 desired concepts with 19 false positives in 23 discharge summaries.

Extracting diagnoses from discharge summaries. Publishing Authors By Initials

W Long,

For similar information science: information services: documentation: vocabulary, controlled: unified medical language system research abstracts see: information science: information services: documentation: vocabulary, controlled: unified medical language system research

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Extracting diagnoses from discharge summaries. Journal Published:

PUBLICATION TYPE: Research Support, N.I.H., Extr

Journal: AMIA ... Annual Symposium proceedings / AMIA Sympo

VOLUME:

Page Numbers: 470-4

Journal Abbreviation:

ISSN: 1559-4076

DAY: 3

MONTH: 12

YEAR: 2005

Extracting diagnoses from discharge summaries. Information

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LANGUAGE: eng

NlmUniqueID: 101209213

Extracting diagnoses from discharge summaries. Keywords Mesh Terms:

KEYWORDS: Unified Medical Language System

MESH TERMS: classification

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Grant and Affiliation Information for Extracting diagnoses from discharge summaries.

AFFILIATION: CSAIL, Massachusetts Institute of Technology, Cambridge, MA, USA.

Country: United States

AGENCY: United States NIBIB

GRANT: R01 EB001659

ACRONYM: EB

MEDLINETA: AMIA Annu Symp Proc

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