Synopsis
In the era of data-driven healthcare, the ability to gather insights from diverse data sources is critical for advancing precision medicine and improving patient outcomes. However, concerns around data privacy and security compliance often hinder the analysis of sensitive health information. Federated Learning offers a great solution by enabling collaborative health intelligence across institutions without requiring data to leave local environments. By training machine learning models on decentralized data while preserving confidentiality, federated learning empowers healthcare stakeholders to build robust and generalizable models. Enabling Collaborative Health Intelligence With Federated Learning explores the confluence of federated learning and artificial intelligence as a blueprint for the future of medical care. This book bridges the gap between cutting-edge technological developments in federated learning and the pressing needs of AI-driven medical care. Covering topics such as health intelligence, data analysis, and data security, this book is an excellent resource for academics, healthcare practitioners, policy makers, industry leaders, and graduate students.
"synopsis" may belong to another edition of this title.
About the Author
Dr. Danish Ather is an accomplished book editor with a robust academic and professional background. Currently as Professor at Amity University in Tashkent, Uzbekistan, Dr. Ather brings over 18 years of experience in teaching, research, and administration. He holds dual Ph.D. degrees in Computer Science and Computer Science & Engineering. His editorial expertise is highlighted through his role as Editor of the proceedings submitted yearly to IEEE USA for the SMART Series conferences. Dr. Ather has authored a book titled "Level up Your Programming with Core Dragon" and published 54 research papers in international journals and conferences, with 15 indexed in Scopus. He is a Senior Member of the IEEE Society and has received numerous awards, including a Certificate of Appreciation from the Ministry of Digital Technologies, Republic of Uzbekistan. His technical proficiency and dedication to advancing knowledge in fields such as IoT, AI, and programming make him a valuable asset in the realm of academic publishing.
"About this title" may belong to another edition of this title.
Search results for Enabling Collaborative Health Intelligence With Federated...
Stock Image
Enabling Collaborative Health Intelligence With Federated Learning
Print on DemandSeller: PBShop.store US, Wood Dale, IL, U.S.A.
Seller rating 5 out of 5 stars
HRD. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Seller Inventory # L1-9798337333069
Stock Image
Enabling Collaborative Health Intelligence With Federated Learning
Print on DemandSeller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 5 out of 5 stars
HRD. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Seller Inventory # L1-9798337333069
Buy New
US$ 302.35
US$ 9.07 shipping
Ships from United Kingdom to U.S.A.
Ships from United Kingdom to U.S.A.
Quantity: Over 20 available
Stock Image
Enabling Collaborative Health Intelligence With Federated Learning (Hardcover)
Print on DemandSeller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Seller rating 5 out of 5 stars
Hardcover. Condition: new. Hardcover. In the era of data-driven healthcare, the ability to gather insights from diverse data sources is critical for advancing precision medicine and improving patient outcomes. However, concerns around data privacy and security compliance often hinder the analysis of sensitive health information. Federated Learning offers a great solution by enabling collaborative health intelligence across institutions without requiring data to leave local environments. By training machine learning models on decentralized data while preserving confidentiality, federated learning empowers healthcare stakeholders to build robust and generalizable models. Enabling Collaborative Health Intelligence With Federated Learning explores the confluence of federated learning and artificial intelligence as a blueprint for the future of medical care. This book bridges the gap between cutting-edge technological developments in federated learning and the pressing needs of AI-driven medical care. Covering topics such as health intelligence, data analysis, and data security, this book is an excellent resource for academics, healthcare practitioners, policy makers, industry leaders, and graduate students. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9798337333069
Stock Image
Enabling Collaborative Health Intelligence With Federated Learning (Hardcover)
Print on DemandSeller: CitiRetail, Stevenage, United Kingdom
Seller rating 5 out of 5 stars
Hardcover. Condition: new. Hardcover. In the era of data-driven healthcare, the ability to gather insights from diverse data sources is critical for advancing precision medicine and improving patient outcomes. However, concerns around data privacy and security compliance often hinder the analysis of sensitive health information. Federated Learning offers a great solution by enabling collaborative health intelligence across institutions without requiring data to leave local environments. By training machine learning models on decentralized data while preserving confidentiality, federated learning empowers healthcare stakeholders to build robust and generalizable models. Enabling Collaborative Health Intelligence With Federated Learning explores the confluence of federated learning and artificial intelligence as a blueprint for the future of medical care. This book bridges the gap between cutting-edge technological developments in federated learning and the pressing needs of AI-driven medical care. Covering topics such as health intelligence, data analysis, and data security, this book is an excellent resource for academics, healthcare practitioners, policy makers, industry leaders, and graduate students. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798337333069
Buy New
US$ 315.73
US$ 49.64 shipping
Ships from United Kingdom to U.S.A.
Ships from United Kingdom to U.S.A.
Quantity: 1 available
Stock Image
Enabling Collaborative Health Intelligence With Federated Learning (Hardcover)
Print on DemandSeller: AussieBookSeller, Truganina, VIC, Australia
Seller rating 5 out of 5 stars
Hardcover. Condition: new. Hardcover. In the era of data-driven healthcare, the ability to gather insights from diverse data sources is critical for advancing precision medicine and improving patient outcomes. However, concerns around data privacy and security compliance often hinder the analysis of sensitive health information. Federated Learning offers a great solution by enabling collaborative health intelligence across institutions without requiring data to leave local environments. By training machine learning models on decentralized data while preserving confidentiality, federated learning empowers healthcare stakeholders to build robust and generalizable models. Enabling Collaborative Health Intelligence With Federated Learning explores the confluence of federated learning and artificial intelligence as a blueprint for the future of medical care. This book bridges the gap between cutting-edge technological developments in federated learning and the pressing needs of AI-driven medical care. Covering topics such as health intelligence, data analysis, and data security, this book is an excellent resource for academics, healthcare practitioners, policy makers, industry leaders, and graduate students. 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. Seller Inventory # 9798337333069
Buy New
US$ 415.14
US$ 37.00 shipping
Ships from Australia to U.S.A.
Ships from Australia to U.S.A.
Quantity: 1 available
Seller Image
Enabling Collaborative Health Intelligence With Federated Learning
Print on DemandSeller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In the era of data-driven healthcare, the ability to gather insights from diverse data sources is critical for advancing precision medicine and improving patient outcomes. However, concerns around data privacy and security compliance often hinder the analysis of sensitive health information. Federated Learning offers a great solution by enabling collaborative health intelligence across institutions without requiring data to leave local environments. By training machine learning models on decentralized data while preserving confidentiality, federated learning empowers healthcare stakeholders to build robust and generalizable models. Enabling Collaborative Health Intelligence With Federated Learning explores the confluence of federated learning and artificial intelligence as a blueprint for the future of medical care. This book bridges the gap between cutting-edge technological developments in federated learning and the pressing needs of AI-driven medical care. Covering topics such as health intelligence, data analysis, and data security, this book is an excellent resource for academics, healthcare practitioners, policy makers, industry leaders, and graduate students. Seller Inventory # 9798337333069
Buy New
US$ 412.74
US$ 76.46 shipping
Ships from Germany to U.S.A.
Ships from Germany to U.S.A.
Quantity: 2 available