Thesis Abstract

Abstract
Skin cancer is a prevalent and potentially life-threatening condition that requires early detection for effective treatment. The use of technology in healthcare has shown promise in improving early detection rates and patient outcomes. This thesis presents the development of a mobile application for skin cancer detection and monitoring to aid both patients and healthcare professionals in identifying potential skin cancer lesions. The mobile application utilizes artificial intelligence algorithms to analyze images of skin lesions captured by users through their smartphone cameras. Through a comprehensive literature review, the project explores existing technologies and methodologies related to skin cancer detection and mobile applications in healthcare. The research methodology employed includes software development, algorithm implementation, and testing using a dataset of skin lesion images. The findings from the study demonstrate the feasibility and effectiveness of the mobile application in accurately identifying potential skin cancer lesions. The discussion of findings delves into the technical aspects of the algorithm, user interface design, and the integration of the application into existing healthcare systems. The significance of this research lies in its potential to facilitate early detection of skin cancer, improve patient outcomes, and reduce healthcare costs associated with late-stage diagnosis. The conclusion summarizes the key findings of the study, highlights the implications for future research and development, and underscores the importance of leveraging technology for enhancing healthcare services. This thesis contributes to the growing field of digital health innovation by presenting a novel solution for skin cancer detection and monitoring through a user-friendly mobile application.

Thesis Overview