In the era of digital healthcare, the convergence of biomedical imaging, informatics, and artificial intelligence (AI) is transforming the way diseases are detected, diagnosed, monitored, and treated. This informative volume explores the latest advances driving this evolution, demonstrating how intelligent technologies are enabling more accurate diagnostics, personalized therapies, and data-driven clinical decision-making.

The volume examines the expanding role of AI in healthcare, including machine learning, deep learning, federated learning, and intelligent decision support systems. It highlights innovations in continuous patient monitoring, smart imaging, pattern recognition, and algorithm-assisted diagnostics, illustrating how computational methods complement clinical expertise. The book also explores advances in biomedical data acquisition and processing, with applications ranging from cardiotocography and chest X-ray analysis to transfer learning, image enhancement, and generative adversarial networks for synthetic medical data.

Emerging technologies receive equal attention, particularly the growing role of digital twins in personalized medicine. By integrating real-time data from medical imaging, wearable sensors, and IoT-enabled devices, digital twins offer new opportunities for predictive modeling, individualized treatment planning, and proactive patient care.

Integrating Biomedical Image Processing and Informatics for Healthcare

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