Computational Intelligence and Modelling Techniques for Disease Detection in Mammogram Images 1st Edition

Computational Intelligence and Modelling Techniques for Disease Detection in Mammogram Images, 1st Edition by D. Jude Hemanth is a definitive, practice-oriented guide for anyone working at the intersection of medical imaging and artificial intelligence. Capturing attention with its timely focus on breast cancer detection, this book translates advanced computational methods into actionable strategies for real-world mammogram analysis.

Delve into clear explanations of image pre-processing, feature extraction, and classification models tailored for mammogram images. The author bridges theory and application by presenting contemporary approaches—such as neural networks, fuzzy systems, and hybrid modeling—alongside case studies and performance evaluation metrics that resonate with radiologists, biomedical engineers, and data scientists.

Designed to inspire confidence, the book emphasizes reproducible techniques that improve sensitivity and specificity in computer-aided diagnosis systems. Whether you are developing clinical decision-support tools, conducting research in medical imaging, or teaching health informatics, you’ll find practical algorithms, comparative insights, and implementation guidance that streamline development and validation across clinical settings.

Ideal for professionals and students in hospitals, research labs, and universities across North America, Europe, Asia and beyond, this resource advances both academic inquiry and clinical practice. Equip yourself with the computational intelligence strategies needed to enhance mammogram interpretation and support earlier disease detection.

Secure a copy today to strengthen your expertise in breast cancer detection, medical image analysis, and computer-aided diagnosis—and join a global movement toward smarter, data-driven screening.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.