Degree

Master of Science in Computer Science

Department

Department of Computer Science

School

School of Mathematics and Computer Science (SMCS)

Date of Submission

Fall 2025

Supervisor

Saiyed Shahab Ahmed, Visiting Faculty, Department of Computer Science, School of Mathematics and Computer Science (SMCS)

Keywords

Diabetic foot ulcers, AI healthcare, early detection, mobile health, diabetic care

Abstract

AI-Based Diabetic Foot Ulcer Detection & Management (AIDFUDM) is an intelligent healthcare platform designed to transform the management of diabetes by offering patients and healthcare providers a reliable, AI-driven solution focused on early detection and ongoing monitoring of Diabetic Foot Ulcers (DFUs) and related conditions. In a healthcare environment often challenged by limited access, inconsistent care, and rising patient loads, AIDFUDM stands out by providing a seamless and accessible tool for proactive diabetic care. Built with a strong emphasis on user needs and medical accuracy, AIDFUDM enables patients to upload foot images directly from their smartphones. Using cutting-edge image classification and object detection models, the app analyzes these images to detect early signs of ulcers and recommends appropriate action. The system also allows doctors and patients to exchange notes, track medical history, and maintain continuity of care, all within a secure and easy-to-use interface. Tailored specifically for the Pakistani healthcare context, AIDFUDM bridges the gap between underserved patients and hospitals. The platform is affordable and features an intuitive design to ensure that even those in remote areas can benefit from timely intervention and medical guidance. By reducing the chances of ulcer complications and amputations through early detection, AIDFUDM aims to enhance quality of life and lower treatment costs.

Document Type

Restricted Access

Submission Type

Research Project

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