Thesis Abstract

Abstract
Skin cancer is a significant public health concern globally due to its increasing incidence and potentially fatal consequences if not detected and treated early. The integration of technology in healthcare has shown promise in improving early detection and monitoring of skin cancer. This thesis presents the development of a mobile application designed for skin cancer detection and monitoring. The mobile application utilizes innovative technologies such as artificial intelligence and image analysis to assist users in identifying suspicious skin lesions and tracking changes over time. Chapter One provides an introduction to the research topic, discussing the background of the study, problem statement, objectives, limitations, scope, significance, structure of the thesis, and definition of terms. Chapter Two offers a comprehensive literature review covering ten key areas related to skin cancer detection, mobile health applications, artificial intelligence in dermatology, and current technologies for skin cancer monitoring. Chapter Three outlines the research methodology employed in the development of the mobile application, including the design process, data collection methods, algorithm development, and usability testing. This chapter also discusses the ethical considerations and limitations of the study. Chapter Four presents an in-depth discussion of the findings from the development and testing of the mobile application. The chapter explores the accuracy of the application in detecting skin lesions, user feedback on usability and functionality, and the potential impact of the application on skin cancer diagnosis and management. Chapter Five concludes the thesis by summarizing the key findings, discussing the implications for clinical practice and future research directions, and offering recommendations for the implementation of the mobile application in real-world settings. The thesis contributes to the field of dermatology by providing a novel approach to skin cancer detection and monitoring using mobile technology, with the potential to enhance early diagnosis and improve patient outcomes.

Thesis Overview