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

Machine Learning (1465) Clinical Information and Decision Making (1407) Nosocomial Infections (20) Electronic Health Records (1053) Natural Language Processing (693) Hygiene and Infection Prevention (317) Infectious Diseases (non-STD/STI) (1575) 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
Article Authors Cited by (19) Tweetations (2) Metrics
All Time | Last Month | Last Six Months | Last Year
There are currently no tweets available for this article within the specified range.