Use of Artificial Intelligence for Skin Cancer Detection and Diagnosis in Dermatology

Thesis Abstract

Abstract
Skin cancer is a significant public health concern worldwide, with early detection being crucial for successful treatment outcomes. The advancement of artificial intelligence (AI) technologies has shown promise in improving the accuracy and efficiency of skin cancer detection and diagnosis in dermatology. This thesis explores the utilization of AI techniques for skin cancer detection and diagnosis, aiming to enhance the capabilities of healthcare professionals in identifying and treating skin cancer cases promptly. The thesis begins with a comprehensive introduction discussing the background of the study, the problem statement, objectives, limitations, scope, significance, and structure of the thesis. The definitions of key terms related to AI, skin cancer, and dermatology are also provided to establish a solid foundation for the study. Chapter Two presents a detailed literature review covering ten key areas related to AI applications in skin cancer detection and diagnosis. The review examines existing studies, methodologies, algorithms, and technologies used in AI-based skin cancer detection systems, highlighting their strengths, weaknesses, and potential for future improvements. Chapter Three outlines the research methodology employed in this study, including data collection, preprocessing, feature selection, model development, and evaluation metrics. Eight key components of the research methodology are discussed to provide a clear understanding of the experimental design and implementation process. In Chapter Four, the findings of the study are extensively discussed, presenting the results of AI models developed for skin cancer detection and diagnosis. The performance metrics, including sensitivity, specificity, accuracy, and area under the curve, are analyzed to evaluate the efficacy of the AI-based system in comparison to traditional diagnostic methods. Finally, Chapter Five offers a conclusion and summary of the thesis, highlighting the key findings, contributions, limitations, and future research directions. The study concludes that AI technologies have the potential to revolutionize skin cancer detection and diagnosis in dermatology by enhancing accuracy, efficiency, and accessibility to healthcare services. In conclusion, this thesis contributes to the growing body of knowledge on the application of AI for skin cancer detection and diagnosis in dermatology. The findings of this study have implications for healthcare professionals, researchers, and policymakers seeking to improve skin cancer outcomes through the integration of innovative technologies. By harnessing the power of AI, the healthcare industry can advance towards more effective strategies for early detection and treatment of skin cancer, ultimately saving lives and improving patient care.