College

College of Engineering and Polymer Science

Date of Last Revision

2025-12-11 06:49:30

Major

Computer Science

Honors Course

498-002

Number of Credits

3

Degree Name

Bachelor of Science in Computer Science

Date of Expected Graduation

Fall 2025

Abstract

SkinRisk AI is an exploration of the opportunities for implementing machine learning (ML) and artificial intelligence (AI) in the medical technology field, specifically in the early detection of skin cancer. This project presents the design, development, and evaluation of a mobile application that allows users to capture images of skin lesions and receive a machine learning assisted risk assessment. The system combines a convolutional neural network (CNN) for image analysis with an intuitive mobile app built using Flutter, FastAPI, and Supabase to deliver real time screening.

Motivated by the rising skin cancer rates and importance of early detection, SkinRisk AI aims to improve healthcare accessibility, raise awareness, and educate users on the importance of seeking professional medical attention. Although this is not meant to be a diagnostic tool, the project demonstrates how modern AI and ML systems can assist individuals in monitoring their skin health and serves as an example for other applications of ML in medical contexts.

Research Sponsor

Zhong-Hui Duan

First Reader

En Cheng

Second Reader

Michael L. Collard

Honors Faculty Advisor

Zhong-Hui Duan

Proprietary and/or Confidential Information

No

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