Thesis Abstract

Abstract
Skin cancer is a significant public health concern worldwide, with early detection being crucial for effective treatment and improved patient outcomes. In recent years, artificial intelligence (AI) has emerged as a promising technology for enhancing diagnostic accuracy in various medical fields, including dermatology. This thesis presents the development of a diagnostic tool for skin cancer detection using artificial intelligence. Chapter One provides an introduction to the research topic, discussing the background of the study, the problem statement, objectives, limitations, scope, significance of the study, and the structure of the thesis. The chapter also includes definitions of key terms related to the project. Chapter Two consists of a comprehensive review of the existing literature on skin cancer detection, artificial intelligence applications in dermatology, and the current state-of-the-art technologies in this field. The literature review covers ten key aspects that inform the development of the diagnostic tool. Chapter Three outlines the research methodology employed in this study. It includes detailed descriptions of the data collection methods, data preprocessing techniques, feature selection processes, the AI model architecture, training and validation procedures, performance evaluation metrics, and ethical considerations. The chapter also discusses the challenges and solutions encountered during the research process. Chapter Four presents a detailed discussion of the findings obtained from the implementation of the diagnostic tool. The chapter analyzes the performance of the AI model in detecting different types of skin cancer lesions, compares the results with existing methods, and discusses the implications of the findings for clinical practice. Chapter Five concludes the thesis by summarizing the key findings, highlighting the contributions of the research, discussing the limitations of the study, and proposing recommendations for future research directions. The chapter emphasizes the potential impact of the developed diagnostic tool on improving early detection rates, reducing misdiagnosis, and enhancing patient care in dermatology. In conclusion, this thesis contributes to the field of dermatology by presenting a novel approach to skin cancer detection through the development of an AI-based diagnostic tool. The research demonstrates the potential of artificial intelligence in improving diagnostic accuracy and efficiency, thereby benefiting both healthcare providers and patients. The findings of this study have implications for advancing the field of dermatology and paving the way for innovative technologies in skin cancer detection and management.

Thesis Overview