Medical Minds and Machine Learning

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Bol A comprehensive guide to technologies and applications of AI in healthcare. It navigates through the foundational principles of machine learning, dives into real-world implementations such as radiology diagnostics, robotic surgery, and predictive analytics, and addresses key topics like NLP of EHRs and AI assisted drug discovery. This volume reviews the convergence of AI and medicine. As healthcare systems face rising demands, clinician shortages, and the complexity of patient data, machine learning and deep learning are stepping in as transformative forces—to improve diagnosis, personalize treatments, and enhance patient outcomes. This book is a comprehensive guide to technologies, applications, and implications of AI in healthcare. It navigates through the foundational principles of machine learning, dives into real-world implementations such as radiology diagnostics, robotic surgery, and predictive analytics, and addresses key topics like natural language processing of EHRs and AI assisted drug discovery. Key Features: Explores how generative AI is revolutionizing diagnostics in fields like radiology, oncology, and pathology, enhancing accuracy and efficiency in patient care. Addresses Ethical, Legal, and Regulatory Considerations. Bridges the Gap Between Technology and Clinical Practice. Highlights Future Trends and Innovations. Fosters Multidisciplinary Collaboration.

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Bol

A comprehensive guide to technologies and applications of AI in healthcare. It navigates through the foundational principles of machine learning, dives into real-world implementations such as radiology diagnostics, robotic surgery, and predictive analytics, and addresses key topics like NLP of EHRs and AI assisted drug discovery. This volume reviews the convergence of AI and medicine. As healthcare systems face rising demands, clinician shortages, and the complexity of patient data, machine learning and deep learning are stepping in as transformative forces—to improve diagnosis, personalize treatments, and enhance patient outcomes. This book is a comprehensive guide to technologies, applications, and implications of AI in healthcare. It navigates through the foundational principles of machine learning, dives into real-world implementations such as radiology diagnostics, robotic surgery, and predictive analytics, and addresses key topics like natural language processing of EHRs and AI assisted drug discovery. Key Features: Explores how generative AI is revolutionizing diagnostics in fields like radiology, oncology, and pathology, enhancing accuracy and efficiency in patient care. Addresses Ethical, Legal, and Regulatory Considerations. Bridges the Gap Between Technology and Clinical Practice. Highlights Future Trends and Innovations. Fosters Multidisciplinary Collaboration.

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Pages: 332, Edition: 1, Hardcover, CRC Press


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  • 9781041212867
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