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Zustand: New. Dr. Sandeep Kumar Mathivanan has a M.S. in software engineering and the M.Tech. (By Research) degree from Vellore Institute of Technology, Vellore, India, in 2016 and 2020, respectively, and a Ph.D. from the School of Information Technology and En.

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Zustand: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.…

Hardcover. Zustand: Brand New. 332 pages. 6.14x0.81x9.21 inches. In Stock.

Zustand: New. Saurav Mallik is a Research Scientist in the Department of Pharmacology and Toxicology, The University of Arizona, Tucson, Arizona, USA. Prior to this, he was Postdoctoral Fellow in Harvard T H Chan School of Public Health, University of Texas Hea.

Buch. Zustand: Neu. Neuware - 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.…

Zustand: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.…

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Hardcover. Zustand: new. Hardcover. 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 forcesto 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. 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 item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Hardcover. Zustand: new. Hardcover. The integration ML with robotics and weaponry is revolutionizing mechanical engineering by enabling intelligent systems that can adapt, learn, and operate autonomously. In robotics, ML allows systems to process vast amounts of data from sensors to make real-time decisions. Robots, whether in industrial settings or autonomous vehicles, can navigate environments, recognize objects, and optimize tasks through reinforcement learning algorithms. In military applications, robotics combined with ML enhances autonomous weapon systems. Unmanned aerial vehicles (UAVs) and autonomous ground systems are increasingly utilized for surveillance, targeting, and even combat roles. These systems employ ML to improve target recognition, threat analysis, and adaptive decision-making in dynamic battle environments . This reduces human risk in conflict zones and can lead to more precise operational outcomes. Mechanical engineering plays a critical role in designing the physical systems that enable robotic mobility, structure, and function. Advanced mechanical systems integrate machine learning for predictive maintenance, fault diagnosis, and condition monitoring in weaponry and industrial robotics.Mechanical engineers design robots with complex actuators, sensors, and control mechanisms that respond to real-time data processed by machine learning algorithms. The combination of robotics, ML, and mechanical engineering is driving the development of next-generation intelligent systems. These innovations not only improve automation but are also crucial for defence systems, manufacturing, and autonomous vehicle technologies. This synergy promises greater efficiency, adaptability, and autonomy in a range of applications.Key Features:Highlights Real-World ApplicationsExplores Advanced AI TechniquesAddresses Ethical and Security ConcernsEquips Readers with Hands-On KnowledgeForecasts Future Technological Trends This book examines robotics in modern weaponry, surveying engineering design, ethical and legal considerations, and machine learning's role in perception, autonomy, and decision support. It emphasizes system safety, human machine interaction, verification and control, and policy frameworks guiding deployment. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Hardcover. Zustand: new. Hardcover. 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 forcesto 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. 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 item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Hardcover. Zustand: new. Hardcover. The integration ML with robotics and weaponry is revolutionizing mechanical engineering by enabling intelligent systems that can adapt, learn, and operate autonomously. In robotics, ML allows systems to process vast amounts of data from sensors to make real-time decisions. Robots, whether in industrial settings or autonomous vehicles, can navigate environments, recognize objects, and optimize tasks through reinforcement learning algorithms. In military applications, robotics combined with ML enhances autonomous weapon systems. Unmanned aerial vehicles (UAVs) and autonomous ground systems are increasingly utilized for surveillance, targeting, and even combat roles. These systems employ ML to improve target recognition, threat analysis, and adaptive decision-making in dynamic battle environments . This reduces human risk in conflict zones and can lead to more precise operational outcomes. Mechanical engineering plays a critical role in designing the physical systems that enable robotic mobility, structure, and function. Advanced mechanical systems integrate machine learning for predictive maintenance, fault diagnosis, and condition monitoring in weaponry and industrial robotics.Mechanical engineers design robots with complex actuators, sensors, and control mechanisms that respond to real-time data processed by machine learning algorithms. The combination of robotics, ML, and mechanical engineering is driving the development of next-generation intelligent systems. These innovations not only improve automation but are also crucial for defence systems, manufacturing, and autonomous vehicle technologies. This synergy promises greater efficiency, adaptability, and autonomy in a range of applications.Key Features:Highlights Real-World ApplicationsExplores Advanced AI TechniquesAddresses Ethical and Security ConcernsEquips Readers with Hands-On KnowledgeForecasts Future Technological Trends This book examines robotics in modern weaponry, surveying engineering design, ethical and legal considerations, and machine learning's role in perception, autonomy, and decision support. It emphasizes system safety, human machine interaction, verification and control, and policy frameworks guiding deployment. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

HRD. Zustand: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Zustand: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Zustand: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Zustand: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Hardcover. Zustand: new. Hardcover. 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 forcesto 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. 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 item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…