Artificial Intelligence and Applications for Disease Diagnosis

Artificial Intelligence and Applications for Disease Diagnosis provides a clear, student-friendly introduction to the rapidly evolving role of AI in modern healthcare. Designed for undergraduate and postgraduate students, research scholars, and faculty members, this book bridges foundational concepts with real-world clinical applications. It explains key AI methods including machine learning, deep learning, computer vision, and intelligent decision-support systems in a straightforward manner that supports both classroom learning and independent study. The book highlights how AI techniques assist in diagnosing a wide range of diseases, from infectious illnesses and neurological disorders to cancer and cardiovascular conditions. Through examples, case insights, and simplified technical discussions, readers gain practical understanding of how medical data are processed, how predictive models are built, and how diagnostic accuracy can be improved using automated tools.

Special emphasis is placed on ethical considerations, data quality, model validation, and the challenges of deploying AI solutions in real clinical environments. Each chapter is structured to encourage critical thinking, problem-solving, and research exploration. By the end, readers will be equipped with the knowledge needed to engage with current trends, contribute to emerging research, and design innovative AI-driven diagnostic solutions. This book serves as a comprehensive guide for anyone aiming to explore the intersection of technology and healthcare, making complex ideas accessible while supporting academic growth and research innovation.