Vol Machine Learning for Medical Applications
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Edited by:
Ranjith Rajamanickam
About this book
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.
Offers a thorough exploration of the intersection between machine learning and medical applications
Addresses critical healthcare challenges such as disease diagnosis, treatment optimization, patient monitoring and personalized medicine
Author / Editor information
R. Ranjith, Amit Sharma, R. Dhivya, India; J. Paulo Davim, Portugal.
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