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Integrated Approach Using Intuitionistic Fuzzy Multicriteria Decision-Making to Support Classifier Selection for

Miguel Ortiz-Barrios1, Ian Cleland2, Mark Donnelly2

  • 1Department of Productivity and Innovation, Universidad de la Costa CUC, 58th street #55-66, Barranquilla, 080002, Colombia, 57 3007239699.

JMIR Rehabilitation and Assistive Technologies
|October 22, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a new method to select assistive technologies for Parkinson disease (PD) patients, improving adoption rates. The approach prioritizes factors like structure and adaptability for better technology integration in healthcare.

Keywords:
Parkinson diseasecombined compromise solutionintuitionistic fuzzy analytic hierarchy processintuitionistic fuzzy decision-making trial and evaluation laboratorytechnology adoption

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Area of Science:

  • Neuroscience
  • Health Informatics
  • Decision Science

Background:

  • Parkinson disease (PD) is a leading neurodegenerative disorder, posing significant healthcare challenges.
  • Assistive technologies (ATs) offer potential for independent living and remote care for PD patients.
  • Variable AT adoption rates necessitate predictive models for effective allocation.

Purpose of the Study:

  • To present a novel hybrid multicriteria decision-making approach for selecting classification algorithms.
  • To support the process of technology adoption for patients with Parkinson disease (PD).

Main Methods:

  • Utilized intuitionistic fuzzy analytic hierarchy process (IF-AHP) to prioritize criteria and subcriteria.
  • Employed intuitionistic fuzzy decision-making trial and evaluation laboratory (IF-DEMATEL) to analyze causal relationships.
  • Applied combined compromise solution (CoCoSo) to rank classifiers for technology adoption.

Main Results:

  • Structure (F5) had the highest priority (weight=0.214); adaptability (F4) was most influential.
  • The J48 decision tree (A3) was identified as the most suitable algorithm for PD technology adoption.
  • The proposed CoCoSo method showed high correlation with alternative methods, validating its accuracy.

Conclusions:

  • The IF-AHP-IF-DEMATEL-CoCoSo approach effectively identifies suitable assistive technologies for PD patients.
  • The methodology considers user adoption factors and technology-specific features for clinical implementation.
  • This approach facilitates better matching of assistive technologies to individual Parkinson disease patient needs.