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

Digital Health Reviews (1289) Machine Learning (1465) Clinical Informatics (1022) Electronic Health Records (1053) Artificial Intelligence (1371) Big Data (240)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/48320, first published .
The Use of Deep Learning and Machine Learning on Longitudinal Electronic Health Records for the Early Detection and Prevention of Diseases: Scoping Review

The Use of Deep Learning and Machine Learning on Longitudinal Electronic Health Records for the Early Detection and Prevention of Diseases: Scoping Review

The Use of Deep Learning and Machine Learning on Longitudinal Electronic Health Records for the Early Detection and Prevention of Diseases: Scoping Review

Authors of this article:

Laura Swinckels1, 2, 3, 4 Author Orcid Image ;   Frank C Bennis5, 6, 7 Author Orcid Image ;   Kirsten A Ziesemer8 Author Orcid Image ;   Janneke F M Scheerman2, 3 Author Orcid Image ;   Harmen Bijwaard3 Author Orcid Image ;   Ander de Keijzer4, 9 Author Orcid Image ;   Josef Jan Bruers1, 10 Author Orcid Image
Article Authors Cited by (1) Tweetations (5) Metrics

Journals

  1. Pan L, Mu L, Lei H, Miao S, Hu X, Tang Z, Chen W, Wang X. Predicting survival benefits of immune checkpoint inhibitor therapy in lung cancer patients: a machine learning approach using real-world data. International Journal of Clinical Pharmacy 2024 View