Predicting outcomes in patients undergoing pancreatectomy using wearable technology and machine learning: Prospective cohort study

Authors

Heidy Cos, Washington University in St. Louis
Dingwen Li, Washington University in St. Louis
Gregory Williams, Washington University in St. Louis
Jeffrey Chininis, Washington University School of Medicine in St. Louis
Ruixuan Dai, Washington University in St. Louis
Jingwen Zhang, Washington University in St. Louis
Rohit Srivastava, Washington University in St. Louis
Lacey Raper, Washington University in St. Louis
Dominic Sanford, Washington University School of Medicine in St. Louis
William Hawkins, Washington University School of Medicine in St. Louis
Chenyang Lu, Washington University in St. Louis
Chet W Hammill, Washington University School of Medicine in St. Louis

Journal

Journal of Medical Internet Research

Publication Date

2021

Volume

23

Issue

3

Document Type

Open Access Publication

DOI

10.2196/23595

Rights and Permissions

Cos H, Li D, Williams G, Chininis J, Dai R, Zhang J, Srivastava R, Raper L, Sanford D, Hawkins W, Lu C, Hammill CW Predicting Outcomes in Patients Undergoing Pancreatectomy Using Wearable Technology and Machine Learning: Prospective Cohort Study J Med Internet Res 2021;23(3):e23595. doi:10.2196/23595. Licensed under Creative Commons Attribution cc-by 2.0

Recommended Citation

Cos, Heidy; Li, Dingwen; Williams, Gregory; Chininis, Jeffrey; Dai, Ruixuan; Zhang, Jingwen; Srivastava, Rohit; Raper, Lacey; Sanford, Dominic; Hawkins, William; Lu, Chenyang; and Hammill, Chet W, "Predicting outcomes in patients undergoing pancreatectomy using wearable technology and machine learning: Prospective cohort study." Journal of Medical Internet Research. 23, 3. (2021).
https://digitalcommons.wustl.edu/open_access_pubs/10271