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

Weijia Chen 1*, MD;  Zhijun Lu 1*, MD, PhD;  Lijue You 2, MS;  Lingling Zhou 3, BSc;  Jie Xu 4, 5, MPhil;  Ken Chen 1, 5, 6, MD, DHM

1 Department of Anesthesiology, Rui Jin Hospital, Luwan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai , CN

2 Department of Informatics, Rui Jin Hospital, Luwan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai , CN

3 Department of Infection Prevention and Control, Rui Jin Hospital, Luwan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai , CN

4 VitalStrategic Research Institute , Shanghai , CN

5 Synyi Research , Shanghai , CN

6 Precision Diagnosis and Image Guided Therapy, Philips Research China , Shanghai , CN

*these authors contributed equally

Corresponding Author:

  • Ken Chen, MD, DHM
  • Department of Anesthesiology
  • Rui Jin Hospital, Luwan Branch
  • Shanghai Jiao Tong University School of Medicine
  • South Chongqing Road, No 149
  • Shanghai
  • CN
  • Phone: 86 021-63864050
  • Email: nutastray@gmail.com