loading page

Analyzing Decision-Making Approaches in Identifying Suspicious Diabetes Patients: A Comparative Study of Rough Set, Soft Set, and Rough set based Bayesian Decision Theory
  • Sarfraz Ahmed,
  • * SwapnilBharadwaj
Sarfraz Ahmed
The Assam Kaziranga University

Corresponding Author:sarfraz@kazirangauniversity.in

Author Profile
* SwapnilBharadwaj
The Assam Kaziranga University
Author Profile

Abstract

This research compares decision-making techniques for diagnosing diabetes, including Bayesian decision theory, rough set theory, and fuzzy soft set theory. It discusses applying Bayesian decision theory and rough set theory, utilizing the latter to approximate three-way regions for patient classification. The study aims to provide effective medication plans by considering uncertainty. It concludes that the Bayesian rough set theory-based method identifies boundary regions for further investigation. It suggests decision-making based on minimum overall cost and provides a framework for more precise medical diagnoses for diabetic patients.
08 Jun 2024Submitted to Journal of Software: Evolution and Process
12 Jun 2024Submission Checks Completed
12 Jun 2024Assigned to Editor
26 Jun 2024Reviewer(s) Assigned