Artificial Intelligence for Skin Cancer Detection and Classification

Thesis Abstract

Abstract
Skin cancer is one of the most common types of cancer and its early detection is crucial for successful treatment. In recent years, artificial intelligence (AI) has emerged as a promising tool for improving the accuracy and efficiency of skin cancer detection and classification. This thesis explores the application of AI in the field of dermatology specifically for skin cancer detection and classification. The primary objective of this research is to develop and evaluate an AI system that can accurately detect and classify different types of skin cancer using images of skin lesions. The study begins with a comprehensive review of existing literature on AI in dermatology, skin cancer detection techniques, and the current state of the art in AI-based skin cancer classification. A novel AI algorithm is proposed and implemented for the automated detection and classification of skin cancer based on dermatoscopic images. The methodology involves data collection, preprocessing, feature extraction, model training, and evaluation. The performance of the developed AI system is assessed using various metrics such as sensitivity, specificity, accuracy, and area under the curve (AUC). The findings of this research demonstrate the potential of AI in improving the accuracy and efficiency of skin cancer detection and classification. The developed AI system shows promising results in terms of accuracy and performance compared to traditional methods. The limitations of the study, including dataset size and diversity, are discussed, along with recommendations for future research. The significance of this study lies in its contribution to the field of dermatology by providing a reliable and efficient tool for early detection and classification of skin cancer. The proposed AI system has the potential to assist dermatologists in making more accurate diagnoses, leading to improved patient outcomes and reduced healthcare costs. Furthermore, the findings of this research contribute to the growing body of knowledge on the application of AI in healthcare and medical imaging. In conclusion, this thesis presents a novel AI-based approach for skin cancer detection and classification, highlighting the potential benefits of integrating AI technology into dermatology practice. The developed AI system demonstrates promising results and lays the foundation for further research and development in the field of AI-driven skin cancer diagnosis.