A framework for the development of an optimized artificial intelligence model for diabetes mellitus prediction and treatment recommendation

Islam, Md Ziarul and Hassan, Mohd Khairul Azmi and Amir Hussin, Amir 'Aatieff (2024) A framework for the development of an optimized artificial intelligence model for diabetes mellitus prediction and treatment recommendation. In: Postgraduate Colloquium 2024 Innovating for A Sustainable Future: Interdisciplinary Approaches In The Digital Era. KICT Publishing, pp. 22-37.

Preview

PDF Download (1MB) | Preview

Abstract

Diabetes mellitus presents a significant public health challenge, especially in Malaysia, with its rapidly increasing prevalence. By 2024, an estimated 20.1% of the Malaysian population will be affected by diabetes, potentially rising to 5 million by 2030. This study presents a framework that leverages the Indian Pima Diabetes dataset to develop and evaluate an optimized artificial intelligence (AI) model for diabetes prediction and treatment guidance. Combining machine learning, deep learning algorithms, and ensemble techniques like model stacking, the framework aims to achieve high prediction accuracy, balancing sensitivity and specificity, to support clinical decision-making. The study also highlights the importance of addressing ethical considerations, data privacy, and algorithmic biases to harness AI's full potential in transforming diabetes care.

Item Type:	Book Chapter
Uncontrolled Keywords:	Diabetes Prediction, Artificial Intelligence, Model Stacking, Pima Diabetes Dataset, Ensemble Learning
Subjects:	T Technology > T Technology (General) T Technology > T Technology (General) > T10.5 Communication of technical information
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Information System Kulliyyah of Information and Communication Technology > Department of Information System
Depositing User:	Dr Mohd Khairul Azmi Hassan
Date Deposited:	02 Jan 2025 11:47
Last Modified:	02 Jan 2025 12:05
URI:	http://irep.iium.edu.my/id/eprint/117193

Actions (login required)

View Item