Applied Mathematics for Healthcare Intelligent Systems: Data Representation, Smart Healthcare, Deep Learning and Medical Imaging

This book offers a comprehensive and interdisciplinary perspective on healthcare intelligent systems, highlighting the growing role of applied mathematics, data-driven methodologies, and artificial intelligence in modern healthcare. The book brings together scholarly contributions that explore how intelligent models, data representations, and computational techniques are applied to healthcare diagnostics, medical imaging, and clinical decision-support systems. The chapters cover a wide range of topics, including medical imaging modalities, data handling and representation, deep learning techniques, explainable and trustworthy artificial intelligence, generative models, three-dimensional reconstruction, performance evaluation metrics, ethical considerations, and emerging trends in healthcare technologies. Through practical insights and real-world case studies, the volume illustrates how intelligent systems support disease detection, diagnosis, and personalized treatment planning. Designed for researchers, graduate students, and professionals in healthcare technology, computer science, and biomedical engineering, this book serves as a valuable reference on intelligent healthcare solutions.