Application of Artificial Intelligence in Skin Cancer Diagnosis and Classification

Thesis Abstract

**Abstract
** Skin cancer is one of the most prevalent types of cancer worldwide, with early detection being crucial for successful treatment. The use of Artificial Intelligence (AI) in dermatology has shown promising results in improving the accuracy and efficiency of skin cancer diagnosis and classification. This thesis investigates the application of AI in the field of dermatology specifically for diagnosing and classifying skin cancer. The research begins with an introduction to the background of the study, highlighting the importance of early detection of skin cancer and the potential benefits of AI in this context. The problem statement identifies the current challenges and limitations faced in traditional methods of skin cancer diagnosis. The objectives of the study are outlined to investigate how AI can enhance the accuracy and efficiency of skin cancer diagnosis and classification. The literature review delves into existing studies and technologies related to AI in dermatology, highlighting the advancements and challenges in the field. Various AI techniques such as machine learning, deep learning, and image analysis are explored in the context of skin cancer diagnosis. The research methodology section details the approach taken to collect and analyze data for this study. It includes the selection of datasets, the development of AI models, and the evaluation criteria used to measure the performance of the AI system in diagnosing and classifying skin cancer. The discussion of findings chapter presents the results of the study, showcasing the effectiveness of the AI system in accurately diagnosing and classifying different types of skin cancer. The limitations and challenges encountered during the research are also discussed, along with potential areas for future research and improvement. In conclusion, the study demonstrates the significant potential of AI in revolutionizing the field of dermatology, particularly in the diagnosis and classification of skin cancer. The findings highlight the importance of integrating AI technologies into clinical practice to enhance the accuracy and efficiency of skin cancer detection. This research contributes to the growing body of knowledge on the application of AI in healthcare and provides valuable insights for healthcare professionals, researchers, and policymakers in the field of dermatology.