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

Formative Evaluation of Digital Health Interventions (2530) Natural Language Processing (717) Electronic Health Records (1076) Methods in Cancer Research (32)

Published on in Vol 6, No 12 (2022): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/43059, first published .
Barriers and Facilitators of Obtaining Social Determinants of Health of Patients With Cancer Through the Electronic Health Record Using Natural Language Processing Technology: Qualitative Feasibility Study With Stakeholder Interviews

Barriers and Facilitators of Obtaining Social Determinants of Health of Patients With Cancer Through the Electronic Health Record Using Natural Language Processing Technology: Qualitative Feasibility Study With Stakeholder Interviews

Barriers and Facilitators of Obtaining Social Determinants of Health of Patients With Cancer Through the Electronic Health Record Using Natural Language Processing Technology: Qualitative Feasibility Study With Stakeholder Interviews

Authors of this article:

Jordan Alpert1 Author Orcid Image ;   Hyehyun (Julia) Kim2 Author Orcid Image ;   Cara McDonnell3 Author Orcid Image ;   Yi Guo3 Author Orcid Image ;   Thomas J George4 Author Orcid Image ;   Jiang Bian3 Author Orcid Image ;   Yonghui Wu3 Author Orcid Image
Article Authors Cited by (4) Tweetations (4) Metrics

Journals

  1. Yu Z, Peng C, Yang X, Dang C, Adekkanattu P, Gopal Patra B, Peng Y, Pathak J, Wilson D, Chang C, Lo-Ciganic W, George T, Hogan W, Guo Y, Bian J, Wu Y. Identifying social determinants of health from clinical narratives: A study of performance, documentation ratio, and potential bias. Journal of Biomedical Informatics 2024;153:104642 View
  2. Roy S, Morrell S, Zhao L, Homayouni R. Large-scale identification of social and behavioral determinants of health from clinical notes: comparison of Latent Semantic Indexing and Generative Pretrained Transformer (GPT) models. BMC Medical Informatics and Decision Making 2024;24(1) View
  3. Baminiwatte R, Torsu B, Scherbakov D, Mollalo A, Obeid J, Alekseyenko A, Lenert L. Machine learning in healthcare citizen science: A scoping review. International Journal of Medical Informatics 2025;195:105766 View