MedPredict: a prototype system for integrated machine learning–based disease prediction

Mohd Abu Bakar, Nur Athirah and Hamidi, Hannah Kamillia and Zainal Azmi, Nurazlin (2026) MedPredict: a prototype system for integrated machine learning–based disease prediction. In: International Conference on Information and Communication Technology for the Muslim World (ICT4M), 26-27 November 2025, Kuala Lumpur.

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Abstract

The rise in chronic and non-communicable diseases (NCDs) such as diabetes, heart disease, kidney conditions, and breast cancer has underscored the need for early diagnosis and preventive strategies. Traditional diagnostic approaches often involve complex procedures and specialist interpretation, delaying timely intervention. This paper presents MedPredict, a prototype of an intelligent, web-based disease prediction system that leverages machine learning to assist in the early detection of multiple health conditions. Developed with an integrated architecture, the prototype includes modules for diabetes, heart disease, breast cancer, and kidney disease, each employing tailored ML algorithms trained on public datasets. Evaluation through functional, integration, and usability testing demonstrated positive outcomes, with prediction accuracies ranging from 76% to 98% and high user satisfaction in terms of interface usability and clarity of results. MedPredict aims to complement clinical decision-making and support public health efforts by providing an accessible, non-invasive tool for proactive healthcare.

Item Type:	Proceeding Paper (Plenary Papers)
Subjects:	T Technology > T Technology (General) > T55.4 Industrial engineering.Management engineering. > T58.5 Information technology
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology > Department of Information System Kulliyyah of Information and Communication Technology > Department of Information System
Depositing User:	Dr Nurazlin Zainal Azmi
Date Deposited:	13 May 2026 11:23
Last Modified:	13 May 2026 11:23
Queue Number:	2026-05-Q3264
URI:	http://irep.iium.edu.my/id/eprint/127489

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