Automated NLP Extraction of Clinical Rationale for Treatment Discontinuation in Breast Cancer.

Journal: JCO clinical cancer informatics

Published Date: May 1, 2021

Abstract

PURPOSE: Key oncology end points are not routinely encoded into electronic medical records (EMRs). We assessed whether natural language processing (NLP) can abstract treatment discontinuation rationale from unstructured EMR notes to estimate toxicity incidence and progression-free survival (PFS).

Authors

Matthew S Alkaitis

CSAIL & IMES, Massachusetts Institute of Technology, Cambridge, MA.
Monica N Agrawal

CSAIL & IMES, Massachusetts Institute of Technology, Cambridge, MA.
Gregory J Riely

Thoracic Oncology Service, Memorial Sloan Kettering Cancer Center, New York, New York.
Pedram Razavi

Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York.
David Sontag

1 Department of Computer Science, New York University , New York, New York.

Keywords

Algorithms Breast Neoplasms Electronic Health Records Female Humans Natural Language Processing Retrospective Studies

External Resources

View on PubMed Access via DOI PubMed (33989016)

Automated NLP Extraction of Clinical Rationale for Treatment Discontinuation in Breast Cancer.

Abstract

Authors

Keywords

External Resources

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