Barnes & Noble Machine Learning for Medical Applications: Computational Drug Discovery, Bioimaging, Smart Biomaterials at Hamilton Place in Chattanooga, TN
Machine Learning for Medical Applications – Volume I provides an in-depth look into the frontier of artificial intelligence in healthcare, bringing together contributions from leading researchers and innovators. This volume focuses on three critical areas: computational drug discovery, advanced bioimaging techniques, and the development of smart biomaterials for medical use. Readers will discover how machine learning is revolutionizing personalized medicine, improving diagnostic accuracy, and enabling the design of AI-driven biomedical sensors and therapeutic systems. With practical insights into algorithmic modeling, drug toxicity prediction, and materials screening, this book bridges the gap between data science and clinical applications. Ideal for professionals, academics, and students in biomedical engineering, computer science, and medical informatics, this book highlights the synergistic potential of machine learning and modern medicine in shaping the future of healthcare.
Machine Learning for Medical Applications – Volume I provides an in-depth look into the frontier of artificial intelligence in healthcare, bringing together contributions from leading researchers and innovators. This volume focuses on three critical areas: computational drug discovery, advanced bioimaging techniques, and the development of smart biomaterials for medical use. Readers will discover how machine learning is revolutionizing personalized medicine, improving diagnostic accuracy, and enabling the design of AI-driven biomedical sensors and therapeutic systems. With practical insights into algorithmic modeling, drug toxicity prediction, and materials screening, this book bridges the gap between data science and clinical applications. Ideal for professionals, academics, and students in biomedical engineering, computer science, and medical informatics, this book highlights the synergistic potential of machine learning and modern medicine in shaping the future of healthcare.
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