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

Theme Issue 2022: Health Natural Language Processing and Applications (CHIP) (27) Machine Learning (1728) Clinical Information and Decision Making (1642) Decision Support for Health Professionals (1336)

Published on in Vol 10, No 11 (2022): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/38053, first published .
A Transfer Learning Approach to Correct the Temporal Performance Drift of Clinical Prediction Models: Retrospective Cohort Study

A Transfer Learning Approach to Correct the Temporal Performance Drift of Clinical Prediction Models: Retrospective Cohort Study

A Transfer Learning Approach to Correct the Temporal Performance Drift of Clinical Prediction Models: Retrospective Cohort Study

Authors of this article:

Xiangzhou Zhang1 Author Orcid Image ;   Yunfei Xue1, 2 Author Orcid Image ;   Xinyu Su1, 2 Author Orcid Image ;   Shaoyong Chen1, 2 Author Orcid Image ;   Kang Liu1, 3 Author Orcid Image ;   Weiqi Chen1 Author Orcid Image ;   Mei Liu4 Author Orcid Image ;   Yong Hu1 Author Orcid Image
Article Authors Cited by (6) Tweetations (2) Metrics

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  2. El Emam K, Leung T, Malin B, Klement W, Eysenbach G. Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Models (CREMLS). Journal of Medical Internet Research 2024;26:e52508 View
  3. Rajagopal A, Ayanian S, Ryu A, Qian R, Legler S, Peeler E, Issa M, Coons T, Kawamoto K. Machine Learning Operations in Health Care: A Scoping Review. Mayo Clinic Proceedings: Digital Health 2024;2(3):421 View
  4. Hamarash M, Ibrahim R, Yaas M, Abdulghani M, Al Mushhadany O. Comparative Effectiveness of Health Communication Strategies in Nursing: A Mixed Methods Study of Internet, mHealth, and Social Media Versus Traditional Methods. JMIR Nursing 2024;7:e55744 View
  5. Meng J, Niu X, Luo C, Chen Y, Li Q, Wei D. Development and Validation of a Machine Learning–Based Early Warning Model for Lichenoid Vulvar Disease: Prediction Model Development Study. Journal of Medical Internet Research 2024;26:e55734 View

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