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

Machine Learning (1056) Clinical Information and Decision Making (950) Nosocomial Infections (13) Electronic Health Records (810) Natural Language Processing (507) Hygiene and Infection Prevention (250) Infectious Diseases (non-STD/STI) (1255) Perioperative Infection Control and Prevention (7)

Published on in Vol 8 , No 6 (2020) :June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/18186, first published .
Artificial Intelligence–Based Multimodal Risk Assessment Model for Surgical Site Infection (AMRAMS): Development and Validation Study

Artificial Intelligence–Based Multimodal Risk Assessment Model for Surgical Site Infection (AMRAMS): Development and Validation Study

Artificial Intelligence–Based Multimodal Risk Assessment Model for Surgical Site Infection (AMRAMS): Development and Validation Study

Authors of this article:

Weijia Chen 1 Author Orcid Image ;   Zhijun Lu 1 Author Orcid Image ;   Lijue You 2 Author Orcid Image ;   Lingling Zhou 3 Author Orcid Image ;   Jie Xu 4, 5 Author Orcid Image ;   Ken Chen 1, 5, 6 Author Orcid Image
Article Authors Cited by (13) Tweetations (2) Metrics

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  9. Kadem M, Garber L, Abdelkhalek M, Al-Khazraji B, Keshavarz-Motamed Z. Hemodynamic Modeling, Medical Imaging, and Machine Learning and Their Applications to Cardiovascular Interventions. IEEE Reviews in Biomedical Engineering 2023;16:403 View
  10. Irgang L, Barth H, Holmén M. Data-Driven Technologies as Enablers for Value Creation in the Prevention of Surgical Site Infections: a Systematic Review. Journal of Healthcare Informatics Research 2023;7(1):1 View
  11. Zhang J, Xue F, Liu S, Liu D, Wu Y, Zhao D, Liu Z, Ma W, Han R, Shan L, Duan X. Risk factors and prediction model for inpatient surgical site infection after elective abdominal surgery. World Journal of Gastrointestinal Surgery 2023;15(3):387 View
  12. Flores-Balado Á, Méndez C, González A, Gutierrez R, de las Casas Cámara G, Cordero B, Arcos J, Pfang B, Martín-Ríos M. Using Artificial Intelligence to Reduce Orthopedic Surgical Site Infection Surveillance Workload: Algorithm Design, Validation, and Implementation in Four Spanish Hospitals. American Journal of Infection Control 2023 View
  13. Rafaqat W, Fatima H, Kumar A, Khan S, Khurram M. Machine Learning Model for Assessment of Risk Factors and Postoperative Day for Superficial vs Deep/Organ-Space Surgical Site Infections. Surgical Innovation 2023:155335062311709 View