Individualised recovery trajectories of patients with impeded mobility, using distance between probability distributions of learnt graphs

Chakrabarty, Dalia, Zhang, Chuqiao and Grosan, Crina (2024) Individualised recovery trajectories of patients with impeded mobility, using distance between probability distributions of learnt graphs. Artificial intelligence in medicine. 103005. ISSN 0933-3657

Metadata

Item Type: Article
Authors/Creators:
  • Chakrabarty, Dalia (dalia.chakrabarty@york.ac.uk)
  • Zhang, Chuqiao
  • Grosan, Crina
Copyright, Publisher and Additional Information:

© 2024 The Authors.
Keywords: Soft random geometric graphs, Probabilisticmetric spaces, Statistical distance/divergence measures, Inter-graph dis-tance, Recovery trajectories, Physical rehabilitation.
Dates:
  • Published: 30 October 2024
  • Accepted: 16 October 2024
Institution: The University of York
Academic Units: The University of York > Faculty of Sciences (York) > Mathematics (York)
Depositing User: Pure (York)
Date Deposited: 04 Dec 2024 12:00
Last Modified: 03 Feb 2025 00:08
Published Version: https://doi.org/10.1016/j.artmed.2024.103005
Status: Published
Refereed: Yes
Identification Number: 10.1016/j.artmed.2024.103005
Open Archives Initiative ID (OAI ID):

Download

Published Version

Filename: 1-s2.0-S0933365724002471-main.pdf

Description: Individualised recovery trajectories of patients with impeded mobility, using distance between probability distributions of learnt graphs

Licence: CC-BY 2.5

CLICK TO DOWNLOAD [thumbnail of Individualised recovery trajectories of patients with impeded mobility, using distance between probability distributions of learnt graphs]

Export

Statistics


CORE (COnnecting REpositories)