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

Decision Support for Health Professionals (1163) Viewpoints and Perspectives (508)

Published on in Vol 8, No 11 (2020): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19612, first published .
Amplifying Domain Expertise in Clinical Data Pipelines

Amplifying Domain Expertise in Clinical Data Pipelines

Amplifying Domain Expertise in Clinical Data Pipelines

Authors of this article:

Protiva Rahman1 Author Orcid Image ;   Arnab Nandi1 Author Orcid Image ;   Courtney Hebert1 Author Orcid Image
Article Authors Cited by (5) Tweetations (4) Metrics

Journals

  1. Kerrigan D, Hullman J, Bertini E. A Survey of Domain Knowledge Elicitation in Applied Machine Learning. Multimodal Technologies and Interaction 2021;5(12):73 View
  2. Oei R, Hsu W, Lee M, Tan N. Using similar patients to predict complication in patients with diabetes, hypertension, and lipid disorder: a domain knowledge-infused convolutional neural network approach. Journal of the American Medical Informatics Association 2023;30(2):273 View
  3. Van Laere S, Muylle K, Dupont A, Cornu P. Machine Learning Techniques Outperform Conventional Statistical Methods in the Prediction of High Risk QTc Prolongation Related to a Drug-Drug Interaction. Journal of Medical Systems 2022;46(12) View
  4. 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
  5. Rahman P, Ye C, Mittendorf K, Lenoue-Newton M, Micheel C, Wolber J, Osterman T, Fabbri D. Accelerated curation of checkpoint inhibitor-induced colitis cases from electronic health records. JAMIA Open 2023;6(1) View