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 (1216) Machine Learning (1401)

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
All Time | Last Month | Last Six Months | Last Year
There are currently no tweets available for this article within the specified range.