Full Description
This book explores the application of artificial intelligence (AI) in diagnosing skin cancer, emphasizing the importance of early detection to improve treatment outcomes. It reviews various Deep Learning (DL) algorithms, with a focus on CNN, to classify skin cancer with higher accuracy than traditional methods. Designed for beginners and experts alike, the book provides a comprehensive understanding of AI techniques and their implementation in healthcare.
• Compares the accuracy of AI-based detection methods with traditional medical practices.
• Covers the basics of AI and its relevance in early disease detection, different types of skin cancer and the critical need for early detection.
• Reviews various DL techniques, focusing on CNN for skin cancer classification.
• Provides step-by-step guidance on implementing AI techniques for skin cancer detection, including programming aspects.
• Includes illustrations and real-world examples of AI in action for early skin cancer detection.
The findings of this study will aid doctors in treating the disease at its onset, preventing future deterioration. This book can be referred to by professionals and researchers.
The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons [Attribution-Non Commercial-No Derivatives (CC BY-NC-ND)] 4.0 license.
Contents
1. Skin Cancer and Causes 2. Artificial Intelligence Tools and Technology 3. AI for Skin Cancer Identification 4. Experimental Analysis and Results 5. Mitigation Remedies and Recommendations 6. Summary, Conclusion, and Future Work
