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

Artificial Intelligence in Surgery and Perioperative Medicine (24) New and Emerging Methods and Tools in Surgery and Anaesthesiology (40) Artificial Intelligence (1214) Machine Learning (1400)

Published on in Vol 6 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/50188, first published .
A New Index for the Quantitative Evaluation of Surgical Invasiveness Based on Perioperative Patients’ Behavior Patterns: Machine Learning Approach Using Triaxial Acceleration

A New Index for the Quantitative Evaluation of Surgical Invasiveness Based on Perioperative Patients’ Behavior Patterns: Machine Learning Approach Using Triaxial Acceleration

A New Index for the Quantitative Evaluation of Surgical Invasiveness Based on Perioperative Patients’ Behavior Patterns: Machine Learning Approach Using Triaxial Acceleration

Authors of this article:

Kozo Nakanishi1 Author Orcid Image ;   Hidenori Goto1 Author Orcid Image
Article Authors Cited by Tweetations (8) Metrics

Kozo Nakanishi   1 , MD, PhD ;   Hidenori Goto   1 , MD

1 Department of General Thoracic Surgery, National Hospital Organization Saitama Hospital, Wako Saitama, Japan

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