Natural Language Processing Improves Identification of Colorectal Cancer Testing in the Electronic Medical Record | Zendy

Joshua C. Denny | Zendy; Neesha N. Choma | Zendy; Josh F. Peterson | Zendy; Randolph A. Miller | Zendy; Lisa Bastarache | Zendy; Ming Li | Zendy; Neeraja B. Peterson | Zendy

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Natural Language Processing Improves Identification of Colorectal Cancer Testing in the Electronic Medical Record

Author(s) -

Joshua C. Denny,

Neesha N. Choma,

Josh F. Peterson,

Randolph A. Miller,

Lisa Bastarache,

Ming Li,

Neeraja B. Peterson

Publication year - 2011

Publication title -

medical decision making

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.393

H-Index - 103

eISSN - 1552-681X

pISSN - 0272-989X

DOI - 10.1177/0272989x11400418

Subject(s) - medicine , medical record , colonoscopy , chart , recall , fecal occult blood , sigmoidoscopy , precision and recall , colorectal cancer , artificial intelligence , natural language processing , medical physics , cancer , computer science , linguistics , statistics , philosophy , mathematics

Difficulty identifying patients in need of colorectal cancer (CRC) screening contributes to low screening rates.

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