Thesis Abstract

Abstract
Skin cancer is one of the most common types of cancer worldwide, and early detection plays a crucial role in successful treatment. With the increasing use of mobile technology, the development of a mobile application for skin cancer detection has become a promising approach to provide accessible and convenient screening tools. This thesis presents the design, development, and evaluation of a mobile application aimed at assisting users in self-screening for skin cancer lesions. Chapter 1 introduces the background of the study, highlighting the significance of early skin cancer detection and the limitations of traditional screening methods. The problem statement addresses the need for a user-friendly and reliable tool for skin cancer detection, leading to the objective of developing a mobile application to fill this gap. The scope of the study defines the target users and the features of the mobile application, while the structure of the thesis outlines the chapters and their content. Finally, the chapter provides definitions of key terms used throughout the thesis. Chapter 2 presents a comprehensive literature review on skin cancer, mobile health applications, and existing technologies for skin cancer detection. The review explores the current landscape of skin cancer detection methods and discusses the potential benefits and challenges of using mobile applications for this purpose. Chapter 3 details the research methodology employed in developing the mobile application, including the design process, data collection methods, and evaluation strategies. The chapter discusses the technical aspects of the application development, user interface design considerations, and the integration of machine learning algorithms for lesion analysis. Chapter 4 presents the findings of the study, including the performance evaluation of the mobile application in detecting skin cancer lesions. The chapter discusses the accuracy, sensitivity, and specificity of the application compared to traditional screening methods. Additionally, user feedback and usability testing results are analyzed to assess the overall effectiveness of the mobile application. Chapter 5 concludes the thesis by summarizing the key findings, discussing the implications of the research, and suggesting future directions for enhancing the mobile application for skin cancer detection. The chapter highlights the contributions of the study to the field of dermatology and mobile health technology, emphasizing the potential impact on improving early detection rates and patient outcomes. In conclusion, the development of a mobile application for skin cancer detection offers a promising solution to address the challenges of traditional screening methods. By leveraging mobile technology and machine learning algorithms, this thesis presents a novel approach to empower users in self-screening for skin cancer lesions, ultimately contributing to early detection, timely treatment, and improved patient care.

Thesis Overview