Open AccessNatural Language Processing to Ascertain Cancer Outcomes From Medical Oncologist Notes
Author(s) -
Kenneth L. Kehl,
Wenxin Xu,
Eva M. Lepisto,
Haitham Elmarakeby,
Michael J. Hassett,
Eliezer M. Van Allen,
Bruce E. Johnson,
Deborah Schrag
Publication year - 2020
Publication title -
jco clinical cancer informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.188
H-Index - 12
ISSN - 2473-4276
DOI - 10.1200/cci.20.00020
Subject(s) - medicine , receiver operating characteristic , hazard ratio , lung cancer , cancer , artificial intelligence , oncology , outcome (game theory) , medical record , disease , machine learning , natural language processing , computer science , confidence interval , mathematics , mathematical economics
Cancer research using electronic health records and genomic data sets requires clinical outcomes data, which may be recorded only in unstructured text by treating oncologists. Natural language processing (NLP) could substantially accelerate extraction of this information.