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

Clinical Information and Decision Making (3850) Clinical Informatics (2365) Decision Support for Health Professionals (2311) Safety and Error Prevention in Health (333) Advanced Data Analytics in eHealth (370) Machine Learning (3303) Postoperative Monitoring and Telemonitoring (256) Artificial Intelligence (4936) Hygiene and Infection Prevention (440)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/57486, first published .
Doctor using tablet for SIRS calculation tool, showing patient data fields

Identification of a Susceptible and High-Risk Population for Postoperative Systemic Inflammatory Response Syndrome in Older Adults: Machine Learning–Based Predictive Model

Identification of a Susceptible and High-Risk Population for Postoperative Systemic Inflammatory Response Syndrome in Older Adults: Machine Learning–Based Predictive Model

Authors of this article:

Haiyan Mai1 Author Orcid Image ;   Yaxin Lu2 Author Orcid Image ;   Yu Fu1 Author Orcid Image ;   Tongsen Luo2 Author Orcid Image ;   Xiaoyue Li2 Author Orcid Image ;   Yihan Zhang2 Author Orcid Image ;   Zifeng Liu2 Author Orcid Image ;   Yuenong Zhang3 Author Orcid Image ;   Shaoli Zhou2 Author Orcid Image ;   Chaojin Chen2, 4 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Li B, Yu S, Liao Y, Yuan H. Early warning for acute pyelonephritis with sepsis: risk prediction model for patients without renal medullary necrosis lesions. Frontiers in Medicine 2026;13 View
  2. Wang X, Yang X, Cheng Y, Chen X. Preoperative inflammatory indicators predict postoperative SIRS after cardiac surgery with cardiopulmonary bypass in older patients. BMC Geriatrics 2026;26(1) View