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

Machine Learning (3167) Clinical Informatics (2262) Clinical Information and Decision Making (3694) Decision Support for Health Professionals (2226) Electronic Health Records (1722) Health Services Research (675) Artificial Intelligence (4757) Nursing Education and Training (314)

Published on in Vol 11 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/45377, first published .
Doctor reassuring smiling patient in hospital room

Predicting Postoperative Hospital Stays Using Nursing Narratives and the Reverse Time Attention (RETAIN) Model: Retrospective Cohort Study

Predicting Postoperative Hospital Stays Using Nursing Narratives and the Reverse Time Attention (RETAIN) Model: Retrospective Cohort Study

Authors of this article:

Sungjoo Han1 Author Orcid Image ;   Yong Bum Kim2 Author Orcid Image ;   Jae Hong No2 Author Orcid Image ;   Dong Hoon Suh2 Author Orcid Image ;   Kidong Kim2 Author Orcid Image ;   Soyeon Ahn1 Author Orcid Image
Article Authors Cited by (1) Tweetations (2) Metrics

Journals

  1. Hong H, Kim S, Ryu B. Enhancing multimodal inpatient fall prediction via nursing statement integration within the OMOP common data model. Scientific Reports 2026;16(1) View