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

Clinical Information and Decision Making (1373) Clinical Informatics (986) Decision Support for Health Professionals (1162) Electronic Health Records (1031) Machine Learning (1433)

Published on in Vol 22, No 8 (2020): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16903, first published .
Machine Learning Model for Risk Prediction of Community-Acquired Acute Kidney Injury Hospitalization From Electronic Health Records: Development and Validation Study

Machine Learning Model for Risk Prediction of Community-Acquired Acute Kidney Injury Hospitalization From Electronic Health Records: Development and Validation Study

Machine Learning Model for Risk Prediction of Community-Acquired Acute Kidney Injury Hospitalization From Electronic Health Records: Development and Validation Study

Authors of this article:

Chien-Ning Hsu1, 2 Author Orcid Image ;   Chien-Liang Liu3 Author Orcid Image ;   You-Lin Tain4 Author Orcid Image ;   Chin-Yu Kuo3 Author Orcid Image ;   Yun-Chun Lin3 Author Orcid Image
Article Authors Cited by (32) Tweetations (8) Metrics

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  21. Lu S, Porter I, Valderas J, Harrison C, Sidey-Gibbons C. Effectiveness of routine provision of feedback from patient‐reported outcome measurements for cancer care improvement: a systematic review and meta-analysis. Journal of Patient-Reported Outcomes 2023;7(1) View
  22. Shi H, Shen Y, Li L. Early prediction of acute kidney injury in patients with gastrointestinal bleeding admitted to the intensive care unit based on extreme gradient boosting. Frontiers in Medicine 2023;10 View
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