Thesis Abstract

Abstract
Skin cancer is one of the most prevalent types of cancer worldwide, with early detection being crucial for effective treatment and improved patient outcomes. The advancement of artificial intelligence (AI) technology has opened up new possibilities for enhancing skin cancer detection through innovative approaches. This thesis explores the development of a smartphone-based skin cancer detection system using AI algorithms to assist in the early diagnosis of skin cancer. The research begins with a comprehensive introduction that highlights the significance of early skin cancer detection and the limitations of existing methods. The background of the study provides a detailed overview of the current landscape of skin cancer diagnosis and the potential benefits of integrating AI technology into smartphone applications for skin cancer detection. The problem statement identifies the challenges faced in traditional skin cancer detection methods and emphasizes the need for a more efficient and accessible approach. The objectives of the study are defined to outline the specific goals and outcomes aimed at achieving the successful implementation of the smartphone-based skin cancer detection system. The limitations of the study are acknowledged to address any constraints that may impact the research findings. The scope of the study delineates the boundaries within which the research will be conducted, focusing on the development and evaluation of the AI-powered skin cancer detection system using smartphone technology. The significance of the study underscores the potential impact of the proposed system in improving early detection rates, reducing healthcare costs, and enhancing patient outcomes. The structure of the thesis provides a roadmap for the reader, outlining the organization of the chapters and key components of the research. The literature review delves into existing research on skin cancer detection, AI algorithms, and smartphone-based healthcare applications to provide a comprehensive overview of the current state-of-the-art in the field. The research methodology section details the approach, data collection methods, AI algorithms used, and evaluation metrics employed in developing the skin cancer detection system. The discussion of findings chapter presents the results of the study, including the performance evaluation of the AI algorithms, user feedback on the smartphone application, and the overall effectiveness of the system in detecting skin cancer. The conclusion and summary chapter provide a comprehensive overview of the research findings, implications for future research, and the potential impact of the smartphone-based skin cancer detection system on clinical practice. In conclusion, this thesis contributes to the advancement of skin cancer detection by leveraging AI technology and smartphone applications to provide a convenient and effective tool for early diagnosis. The findings of this research have the potential to revolutionize skin cancer screening practices, improve patient outcomes, and ultimately save lives.

Thesis Overview