Machine Learning for Medical Applications

Beschreibung

Machine Learning for Medical Applications – Volume II delves into the intersection of artificial intelligence, computer vision, and healthcare, offering a comprehensive exploration of how machine learning is revolutionizing disease detection and diagnostics. With a focus on deep learning methods, the volume covers a wide spectrum of innovations including medical image segmentation, predictive modeling, tissue engineering, smart biomaterials, and personalized implant design through 3D printing. Contributors from academia and industry present state-of-the-art applications involving quantum dot functionalization, AI-enhanced diagnostic materials, and real-time image analysis. Each chapter provides both foundational knowledge and practical insight into how advanced algorithms can drive medical breakthroughs. Ideal for medical technologists, data scientists, biomedical engineers, and clinical practitioners, this volume emphasizes the role of machine learning in developing faster, smarter, and more accurate diagnostic tools for the next generation of personalized medicine.

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Ranjith Rajamanickam

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Materialwissenschaft Medizinische Anwendungen Maschinelles Lernen Innovation im Gesundheitswesen Machine Learning Medical Applications Material Science Healthcare Innovation

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