Unveiling the root causes of diabetes using explainable AI

Title

Unveiling the root causes of diabetes using explainable AI

Creator

Banu, P.K. Nizar; Azar, Ahmad Taher; Kamal, Nashwa Ahmad

Description

Diabetes is a non-communicable wide spread disease across the world. To investigate the risky factors that are associated with diabetes, and to start early and customized treatment, researchers are fascinated to explore existing machine learning or deep learning models and to develop more reliable algorithms. The advancement in technology and the increase in world population is an enriching source to prompt and explore the factors that decide a person to be diabetic. Several algorithms and approaches are in place to address these factors but are lacking in emphasizing with more interpretable features which convinces patent to trust the medicine, treatment, and have meaningful conversation with the physicians and artificially intelligent systems. To encourage the participation of people with diabetes for customized treatment and considering societal needs, this chapter explores the possibility of Explainable Artificial Intelligence (XAI) in diabetes detection and figuring out the significant features that dominate diabetes. 2025 Elsevier Inc. All rights reserved.

Source

Explainable AI in Healthcare Imaging for Medical Diagnoses: Digital Revolution of Artificial Intelligence;pp.365-387

Date

01-01-2025

Publisher

Elsevier

Subject

Classification; Diabetes; Machine learning; Random forest; SHAP; XAI

Coverage

Banu P.K.N., Department of Computer Science, CHRIST (Deemed to be University) Central Campus, Karnataka, Bangalore, India; Azar A.T., College of Computer and Information Sciences, Prince Sultan University, Riyadh, Saudi Arabia, Automated Systems and Soft Computing Lab (ASSCL), Prince Sultan University, Riyadh, Saudi Arabia, Faculty of Computers and Artificial Intelligence, Benha University, Benha, Egypt; Kamal N.A., Faculty of Engineering, Cairo University, Giza, Egypt

Rights

Restricted Access; Hardcopy may be available in the library

Relation

ISBN: 978-044323979-3; 978-044323978-6;

Format

online

Language

English

Type

Book chapter

Identifier

https://doi.org/10.1016/B978-0-443-23979-3.00015-4

https://www.scopus.com/pages/publications/105011242189?origin=resultslist