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Aggiungi al carrelloCondizione: 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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Lingua: Inglese
Editore: Taylor & Francis Ltd Jul 2026, 2026
ISBN 10: 1041212860 ISBN 13: 9781041212867
Da: AHA-BUCH GmbH, Einbeck, Germania
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Aggiungi al carrelloBuch. Condizione: 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.
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Da: Books Puddle, New York, NY, U.S.A.
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Aggiungi al carrelloHardback. Condizione: New. In an era defined by digital connectivity, securing sensitive information against cyber threats is a pressing concern. As digital transmission systems advance, so do the methods of intrusion and data theft. Traditional security measures often need to catch up in safeguarding against sophisticated cyber-attacks. This book presents a timely solution by integrating steganography, the ancient art of concealing information, with cutting-edge deep learning techniques. By blending these two technologies, the book offers a comprehensive approach to fortifying the security of digital communication channels. Enhancing Steganography Through Deep Learning Approaches addresses critical issues in national information security, business and personal privacy, property security, counterterrorism, and internet security. It thoroughly explores steganography's application in bolstering security across various domains. Readers will gain insights into the fusion of deep learning and steganography for advanced encryption and data protection, along with innovative steganographic techniques for securing physical and intellectual property. The book also delves into real-world examples of thwarting malicious activities using deep learning-enhanced steganography. This book is tailored for academics and researchers in Artificial Intelligence, postgraduate students seeking in-depth knowledge in AI and deep learning, smart computing practitioners, data analysis professionals, and security sector professionals. It is a valuable resource for those looking to incorporate advanced security measures into their products and services. With a focus on practical insights and real-world applications, this book is an essential guide for understanding and implementing steganography and deep learning techniques to enhance security in digital transmission systems.
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EUR 286,80
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Aggiungi al carrelloHardcover. Condizione: Brand New. 352 pages. 11.02x8.66x2.76 inches. In Stock.
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EUR 276,15
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Aggiungi al carrelloHardback. Condizione: New. In an era defined by digital connectivity, securing sensitive information against cyber threats is a pressing concern. As digital transmission systems advance, so do the methods of intrusion and data theft. Traditional security measures often need to catch up in safeguarding against sophisticated cyber-attacks. This book presents a timely solution by integrating steganography, the ancient art of concealing information, with cutting-edge deep learning techniques. By blending these two technologies, the book offers a comprehensive approach to fortifying the security of digital communication channels. Enhancing Steganography Through Deep Learning Approaches addresses critical issues in national information security, business and personal privacy, property security, counterterrorism, and internet security. It thoroughly explores steganography's application in bolstering security across various domains. Readers will gain insights into the fusion of deep learning and steganography for advanced encryption and data protection, along with innovative steganographic techniques for securing physical and intellectual property. The book also delves into real-world examples of thwarting malicious activities using deep learning-enhanced steganography. This book is tailored for academics and researchers in Artificial Intelligence, postgraduate students seeking in-depth knowledge in AI and deep learning, smart computing practitioners, data analysis professionals, and security sector professionals. It is a valuable resource for those looking to incorporate advanced security measures into their products and services. With a focus on practical insights and real-world applications, this book is an essential guide for understanding and implementing steganography and deep learning techniques to enhance security in digital transmission systems.
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2026
ISBN 10: 1041212860 ISBN 13: 9781041212867
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condizione: 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.
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2026
ISBN 10: 1041212860 ISBN 13: 9781041212867
Da: CitiRetail, Stevenage, Regno Unito
EUR 160,50
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Aggiungi al carrelloHardcover. Condizione: 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.
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EUR 204,26
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Aggiungi al carrelloPAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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EUR 214,51
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Aggiungi al carrelloPAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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EUR 242,17
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Aggiungi al carrelloHRD. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Da: PBShop.store US, Wood Dale, IL, U.S.A.
EUR 255,01
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Aggiungi al carrelloHRD. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Da: preigu, Osnabrück, Germania
EUR 226,25
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Enhancing Steganography Through Deep Learning Approaches | Vijay Kumar (u. a.) | Taschenbuch | Englisch | 2024 | IGI Global | EAN 9798369349403 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 270,08
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In an era defined by digital connectivity, securing sensitive information against cyber threats is a pressing concern. As digital transmission systems advance, so do the methods of intrusion and data theft. Traditional security measures often need to catch up in safeguarding against sophisticated cyber-attacks. This book presents a timely solution by integrating steganography, the ancient art of concealing information, with cutting-edge deep learning techniques. By blending these two technologies, the book offers a comprehensive approach to fortifying the security of digital communication channels. Enhancing Steganography Through Deep Learning Approaches addresses critical issues in national information security, business and personal privacy, property security, counterterrorism, and internet security. It thoroughly explores steganography's application in bolstering security across various domains. Readers will gain insights into the fusion of deep learning and steganography for advanced encryption and data protection, along with innovative steganographic techniques for securing physical and intellectual property. The book also delves into real-world examples of thwarting malicious activities using deep learning-enhanced steganography. This book is tailored for academics and researchers in Artificial Intelligence, postgraduate students seeking in-depth knowledge in AI and deep learning, smart computing practitioners, data analysis professionals, and security sector professionals.