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

Assistive Technologies (150) Neurology and Neurosciences (286) Usability and Technology Use Studies with Elder Subjects (271) Machine Learning (2076) Tools, Programs and Algorithms (376) Cognitive and Neurorehabilitation (349) mHealth for Rehabilitation (352) Clinical Information and Decision Making (1915)

Published on in Vol 11 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/57940, first published .
Integrated Approach Using Intuitionistic Fuzzy Multicriteria Decision-Making to Support Classifier Selection for Technology Adoption in Patients with Parkinson Disease: Algorithm Development and Validation

Integrated Approach Using Intuitionistic Fuzzy Multicriteria Decision-Making to Support Classifier Selection for Technology Adoption in Patients with Parkinson Disease: Algorithm Development and Validation

Integrated Approach Using Intuitionistic Fuzzy Multicriteria Decision-Making to Support Classifier Selection for Technology Adoption in Patients with Parkinson Disease: Algorithm Development and Validation

Authors of this article:

Miguel Ortiz-Barrios1 Author Orcid Image ;   Ian Cleland2 Author Orcid Image ;   Mark Donnelly2 Author Orcid Image ;   Muhammet Gul3 Author Orcid Image ;   Melih Yucesan4 Author Orcid Image ;   Genett Isabel Jiménez-Delgado5 Author Orcid Image ;   Chris Nugent2 Author Orcid Image ;   Stephany Madrid-Sierra1 Author Orcid Image
Article Authors Cited by (3) Tweetations (1) Metrics

Journals

  1. Munzesheimer S, Siu T, Yacinthe D, Garcia-Casals M, Haq I, Shpiner D. An Interdisciplinary Approach to Assistive Technology for Parkinson’s Disease Dementia. Clinical Interventions in Aging 2025;Volume 20:1253 View
  2. Wei L. Research on Modularized Design of Urban Public Facilities Based on Interaction Concepts. Applied Mathematics and Nonlinear Sciences 2025;10(1) View
  3. Mohammed T, Xinying C, Albahri A, Alnoor A, Khai Wah K. A Novel Trusted Framework for Orthopedic Disease Detection With Reliability Against Adversarial Attacks. IEEE Access 2025;13:160193 View