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

Artificial Intelligence in Surgery and Perioperative Medicine (30) New and Emerging Methods and Tools in Surgery and Anaesthesiology (44) Artificial Intelligence (1556) Machine Learning (1585)

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 (1) Tweetations (8) Metrics

Journals

  1. Becker M, Hurkmans H, Verhaar J, Bussmann J. Monitoring postures and motions of hospitalized patients using sensor technology: a scoping review. Annals of Medicine 2024;56(1) View