Innovative Solutions for Real-Time Diabetic Foot Ulcers Detection App

Project Code :TCMAKO37

Objective

The objective is to transform ulcer detection by creating a user-friendly application. Utilizing deep learning, the app swiftly analyzes user-captured ulcer images, classifying them as normal or severe and providing instant feedback. Timely notifications for severe cases ensure prompt medical attention, fostering proactive healthcare and improving overall patient outcomes through early detection and intervention.

Abstract

This application aims to revolutionize ulcer detection through a user-friendly interface. Users can capture a photo of a potential ulcer, and a deep learning model embedded in the application analyzes the image to predict the severity of the ulcer. The model classifies ulcers into normal or severe categories, providing instant feedback to the user. In cases of severe ulcers, the application sends a timely notification to the user, alerting them of the condition and advising prompt medical attention. By combining image recognition technology and notifications, this innovative solution enhances early ulcer detection and encourages proactive healthcare management, ultimately contributing to improved patient outcomes.

KEYWORDS: Ulcer detection, User-friendly interface, Deep learning model, Image analysis, Severity prediction, Healthcare management.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.