CC BY-NC-ND 4.0 · Appl Clin Inform 2017; 08(02): 447-453
DOI: 10.4338/ACI-2017-01-IE-0018
Invited Editorial
Schattauer GmbH

Canary: An NLP Platform for Clinicians and Researchers

Shervin Malmasi
1  Brigham and Women’s Hospital, Boston, MA
,
Nicolae L. Sandor
2  Boston University, Boston, MA
,
Naoshi Hosomura
1  Brigham and Women’s Hospital, Boston, MA
,
Matt Goldberg
3  Harvard University, Boston, MA
,
Stephen Skentzos
4  Kiip, Inc., San Francisco, CA
,
Alexander Turchin
1  Brigham and Women’s Hospital, Boston, MA
› Author Affiliations
Further Information

Publication History

received: 17 January 2017

accepted: 22 February 2017

Publication Date:
21 December 2017 (online)

  

Summary

Information Extraction methods can help discover critical knowledge buried in the vast repositories of unstructured clinical data. However, these methods are underutilized in clinical research, potentially due to the absence of free software geared towards clinicians with little technical expertise. The skills required for developing/using such software constitute a major barrier for medical researchers wishing to employ these methods. To address this, we have developed Canary, a free and open-source solution designed for users without natural language processing (NLP) or software engineering experience. It was designed to be fast and work out of the box via a user-friendly graphical interface.

Citation: Malmasi S, Sandor NL, Hosomura N, Goldberg M, Skentzos S, Turchin A. Canary: an NLP platform for clinicians and researchers. Appl Clin Inform 2017; 8: 447–453 https://doi.org/10.4338/ACI-2017-01-IE-0018

Protection of Human Subjects

All research projects involving analysis of narrative electronic medical record data by Canary were reviewed by Partners HealthCare Human Research Committee, and the requirement for written informed consent was waived.