This paper is in the following e-collection/theme issue:

Theme Issue 2022: Health Natural Language Processing and Applications (CHIP) (27) Electronic Health Records (961) Clinical Information and Decision Making (1314) Natural Language Processing (636) Clinical Informatics (904) Decision Support for Health Professionals (1127) Viewpoints and Perspectives (483)

Published on in Vol 11 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37805, first published .
Practical Considerations for Developing Clinical Natural Language Processing Systems for Population Health Management and Measurement

Practical Considerations for Developing Clinical Natural Language Processing Systems for Population Health Management and Measurement

Practical Considerations for Developing Clinical Natural Language Processing Systems for Population Health Management and Measurement

Authors of this article:

Suzanne Tamang1, 2 Author Orcid Image ;   Marie Humbert-Droz1 Author Orcid Image ;   Milena Gianfrancesco3 Author Orcid Image ;   Zara Izadi3 Author Orcid Image ;   Gabriela Schmajuk3 Author Orcid Image ;   Jinoos Yazdany3 Author Orcid Image
Article Authors Cited by (6) Tweetations (19) Metrics

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  2. Naseri H, Skamene S, Tolba M, Faye M, Ramia P, Khriguian J, David M, Kildea J. A Scalable Radiomics- and Natural Language Processing–Based Machine Learning Pipeline to Distinguish Between Painful and Painless Thoracic Spinal Bone Metastases: Retrospective Algorithm Development and Validation Study. JMIR AI 2023;2:e44779 View
  3. Pillai M, Griffin A, Kronk C, McCall T. Toward Community-Based Natural Language Processing (CBNLP): Cocreating With Communities. Journal of Medical Internet Research 2023;25:e48498 View
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