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

Machine Learning (1501) Clinical Information and Decision Making (1434) Nosocomial Infections (21) Electronic Health Records (1068) Natural Language Processing (706) Hygiene and Infection Prevention (325) Infectious Diseases (non-STD/STI) (1592) Perioperative Infection Control and Prevention (8)

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 Chen1 Author Orcid Image ;   Zhijun Lu1 Author Orcid Image ;   Lijue You2 Author Orcid Image ;   Lingling Zhou3 Author Orcid Image ;   Jie Xu4, 5 Author Orcid Image ;   Ken Chen1, 5, 6 Author Orcid Image
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