Development of an AI-powered mobile application for early detection of skin cancer

Thesis Abstract

Abstract
Skin cancer is a significant global health concern with increasing incidence rates worldwide. Early detection is crucial for successful treatment outcomes, yet many cases go undiagnosed until advanced stages. The use of artificial intelligence (AI) in healthcare has shown promising results in various applications, including medical imaging and diagnostics. This thesis presents the development of an AI-powered mobile application for the early detection of skin cancer. The primary aim of this research is to leverage AI technology to enhance the accuracy and efficiency of skin cancer detection through a user-friendly mobile application. The application will utilize machine learning algorithms to analyze images of skin lesions captured by smartphone cameras. By incorporating a deep learning model trained on a large dataset of annotated skin images, the application will provide real-time feedback on the likelihood of a lesion being malignant. Chapter 1 provides an introduction to the research topic, background information on skin cancer, the problem statement, objectives of the study, limitations, scope, significance of the study, structure of the thesis, and definition of key terms. Chapter 2 presents a comprehensive literature review on skin cancer, AI in healthcare, mobile health applications, and existing technologies for skin cancer detection. Chapter 3 outlines the research methodology, including data collection, preprocessing, model training, evaluation metrics, and validation techniques. The chapter also discusses ethical considerations and data security measures implemented in the development of the mobile application. In Chapter 4, the findings of the study are presented and discussed in detail. The performance of the AI model in detecting skin cancer lesions is evaluated based on sensitivity, specificity, and overall accuracy. The usability and user experience of the mobile application are also assessed through user feedback and testing. Finally, Chapter 5 concludes the thesis with a summary of the research outcomes, implications for clinical practice, limitations of the study, recommendations for future research, and the overall contribution of the AI-powered mobile application to early skin cancer detection. The thesis underscores the potential of AI technology to revolutionize dermatological care and improve patient outcomes through early detection and intervention.