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

Artificial Intelligence (1377) Machine Learning (1471) Clinical Information and Decision Making (1411) Decision Support for Health Professionals (1191) Research Instruments, Questionnaires, and Tools (578) Tools, Programs and Algorithms (267) Safety and Error Prevention in Health (204)

Published on in Vol 23, No 9 (2021): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27098, first published .
Machine Learning Analysis of Time-Dependent Features for Predicting Adverse Events During Hemodialysis Therapy: Model Development and Validation Study

Machine Learning Analysis of Time-Dependent Features for Predicting Adverse Events During Hemodialysis Therapy: Model Development and Validation Study

Machine Learning Analysis of Time-Dependent Features for Predicting Adverse Events During Hemodialysis Therapy: Model Development and Validation Study

Authors of this article:

Yi-Shiuan Liu1, 2, 3, 4 Author Orcid Image ;   Chih-Yu Yang1, 2, 5, 6 Author Orcid Image ;   Ping-Fang Chiu7 Author Orcid Image ;   Hui-Chu Lin2 Author Orcid Image ;   Chung-Chuan Lo8 Author Orcid Image ;   Alan Szu-Han Lai2 Author Orcid Image ;   Chia-Chu Chang9, 10 Author Orcid Image ;   Oscar Kuang-Sheng Lee1, 2, 11 Author Orcid Image
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