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

Tools, Programs and Algorithms (605) Clinical Informatics (2381) Design of Processes and Workflows (300) Machine Learning (3327) E-Health / Health Services Research and New Models of Care (1223) Validity, Reliability, and Bias (148)

Published on in Vol 12 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/58978, first published .
Medical team rushes patient on gurney down hospital hallway

Evaluating the Bias in Hospital Data: Automatic Preprocessing of Patient Pathways Algorithm Development and Validation Study

Evaluating the Bias in Hospital Data: Automatic Preprocessing of Patient Pathways Algorithm Development and Validation Study

Authors of this article:

Laura Uhl1 Author Orcid Image ;   Vincent Augusto1 Author Orcid Image ;   Benjamin Dalmas1 Author Orcid Image ;   Youenn Alexandre2 Author Orcid Image ;   Paolo Bercelli2 Author Orcid Image ;   Fanny Jardinaud3 Author Orcid Image ;   Saber Aloui4 Author Orcid Image
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Journals

  1. Rahman S, Zaki A, Huda N, Faisal A, Wei L. Interpretable Machine Learning Model for Detecting Clinical Pathway Deviations in Hospitalized Patients Using Order Sequences, Vital Sign Trends, Laboratory Monitoring Frequency, and Provider Decision Patterns. Journal of Health Informatics and Digital Systems 2024;4(2) View