Firoz mridha (30 resultados)

Hardcover. Condición: new. Hardcover. This book offers an in-depth exploration of federated learning (FL), a groundbreaking approach that facilitates collaborative data analysis while ensuring patient privacy and data security. As healthcare systems worldwide generate vast amounts of data, the challenge lies in harnessing this information without compromising confidentiality. Federated learning addresses this by allowing multiple institutions to collaborate on machine learning models without sharing sensitive data. In this context, the authors delve into the foundational principles of FL, illustrating how it enables the aggregation of decentralized data to improve diagnostic accuracy, develop personalized treatment plans, and enhance overall healthcare outcomes. The authors present real-world applications across various medical fields, from predictive analytics in chronic disease management to precision medicine and beyond. Additionally, the authors discuss the ethical and regulatory landscapes, providing insights into the challenges and solutions associated with implementing FL in healthcare. This book is designed for a diverse audience, including researchers, healthcare practitioners, data scientists, and policymakers. It aims to bridge the gap between cutting-edge technology and practical medical applications, offering a comprehensive guide to leveraging FL for healthcare innovation. mso-ansi-language: EN-US;">This book offers an in-depth exploration of federated learning (FL), a groundbreaking approach that facilitates collaborative data analysis while ensuring patient privacy and data security. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condición: New.

Hardcover. Condición: new. Hardcover. This book offers an in-depth exploration of federated learning (FL), a groundbreaking approach that facilitates collaborative data analysis while ensuring patient privacy and data security. As healthcare systems worldwide generate vast amounts of data, the challenge lies in harnessing this information without compromising confidentiality. Federated learning addresses this by allowing multiple institutions to collaborate on machine learning models without sharing sensitive data. In this context, the authors delve into the foundational principles of FL, illustrating how it enables the aggregation of decentralized data to improve diagnostic accuracy, develop personalized treatment plans, and enhance overall healthcare outcomes. The authors present real-world applications across various medical fields, from predictive analytics in chronic disease management to precision medicine and beyond. Additionally, the authors discuss the ethical and regulatory landscapes, providing insights into the challenges and solutions associated with implementing FL in healthcare. This book is designed for a diverse audience, including researchers, healthcare practitioners, data scientists, and policymakers. It aims to bridge the gap between cutting-edge technology and practical medical applications, offering a comprehensive guide to leveraging FL for healthcare innovation. mso-ansi-language: EN-US;">This book offers an in-depth exploration of federated learning (FL), a groundbreaking approach that facilitates collaborative data analysis while ensuring patient privacy and data security. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Condición: New.

Condición: As New. Unread book in perfect condition.

Condición: As New. Unread book in perfect condition.

Condición: New.

Hardcover. Condición: new. Hardcover. This book features high-quality research papers presented at the International Conference on Deep Learning and Visual Artificial Intelligence (ICDLAI), held at Government Engineering College Bikaner, Bikaner, India, during March 1617, 2024. The book presents diverse range of topics, including advanced deep learning techniques, neural networks, image processing, object detection, and pattern recognition. This book features high-quality research papers presented at the International Conference on Deep Learning and Visual Artificial Intelligence (ICDLAI), held at Government Engineering College Bikaner, Bikaner, India, during March 1617, 2024. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condición: New. 2024th edition NO-PA16APR2015-KAP.

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book offers an in-depth exploration of federated learning (FL), a groundbreaking approach that facilitates collaborative data analysis while ensuring patient privacy and data security. As healthcare systems worldwide generate vast amounts of data, the challenge lies in harnessing this information without compromising confidentiality. Federated learning addresses this by allowing multiple institutions to collaborate on machine learning models without sharing sensitive data. In this context, the authors delve into the foundational principles of FL, illustrating how it enables the aggregation of decentralized data to improve diagnostic accuracy, develop personalized treatment plans, and enhance overall healthcare outcomes. The authors present real-world applications across various medical fields, from predictive analytics in chronic disease management to precision medicine and beyond. Additionally, the authors discuss the ethical and regulatory landscapes, providing insights into the challenges and solutions associated with implementing FL in healthcare. This book is designed for a diverse audience, including researchers, healthcare practitioners, data scientists, and policymakers. It aims to bridge the gap between cutting-edge technology and practical medical applications, offering a comprehensive guide to leveraging FL for healthcare innovation.…

Hardcover. Condición: new. Hardcover. This book offers an in-depth exploration of federated learning (FL), a groundbreaking approach that facilitates collaborative data analysis while ensuring patient privacy and data security. As healthcare systems worldwide generate vast amounts of data, the challenge lies in harnessing this information without compromising confidentiality. Federated learning addresses this by allowing multiple institutions to collaborate on machine learning models without sharing sensitive data. In this context, the authors delve into the foundational principles of FL, illustrating how it enables the aggregation of decentralized data to improve diagnostic accuracy, develop personalized treatment plans, and enhance overall healthcare outcomes. The authors present real-world applications across various medical fields, from predictive analytics in chronic disease management to precision medicine and beyond. Additionally, the authors discuss the ethical and regulatory landscapes, providing insights into the challenges and solutions associated with implementing FL in healthcare. This book is designed for a diverse audience, including researchers, healthcare practitioners, data scientists, and policymakers. It aims to bridge the gap between cutting-edge technology and practical medical applications, offering a comprehensive guide to leveraging FL for healthcare innovation. mso-ansi-language: EN-US;">This book offers an in-depth exploration of federated learning (FL), a groundbreaking approach that facilitates collaborative data analysis while ensuring patient privacy and data security. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Hardcover. Condición: Brand New. 500 pages. 9.25x6.10x9.49 inches. In Stock.

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book features high-quality research papers presented at the International Conference on Deep Learning and Visual Artificial Intelligence (ICDLAI), held at Government Engineering College Bikaner, Bikaner, India, during March 16-17, 2024. The book presents diverse range of topics, including advanced deep learning techniques, neural networks, image processing, object detection, and pattern recognition. …

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book features high-quality research papers presented at the International Conference on Deep Learning and Visual Artificial Intelligence (ICDLAI), held at Government Engineering College Bikaner, Bikaner, India, during March 16-17, 2024. The book presents diverse range of topics, including advanced deep learning techniques, neural networks, image processing, object detection, and pattern recognition.…

Condición: new. Questo è un articolo print on demand.

Hardcover. Condición: Brand New. 250 pages. 9.26x6.11x9.21 inches. In Stock. This item is printed on demand.

Condición: new. Questo è un articolo print on demand.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.

Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book offers an in-depth exploration of federated learning (FL), a groundbreaking approach that facilitates collaborative data analysis while ensuring patient privacy and data security. As healthcare systems worldwide generate vast amounts of data, the challenge lies in harnessing this information without compromising confidentiality. Federated learning addresses this by allowing multiple institutions to collaborate on machine learning models without sharing sensitive data. In this context, the authors delve into the foundational principles of FL, illustrating how it enables the aggregation of decentralized data to improve diagnostic accuracy, develop personalized treatment plans, and enhance overall healthcare outcomes. The authors present real-world applications across various medical fields, from predictive analytics in chronic disease management to precision medicine and beyond. Additionally, the authors discuss the ethical and regulatory landscapes, providing insights into the challenges and solutions associated with implementing FL in healthcare. This book is designed for a diverse audience, including researchers, healthcare practitioners, data scientists, and policymakers. It aims to bridge the gap between cutting-edge technology and practical medical applications, offering a comprehensive guide to leveraging FL for healthcare innovation. 244 pp. Englisch.…

Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book offers an in-depth exploration of federated learning (FL), a groundbreaking approach that facilitates collaborative data analysis while ensuring patient privacy and data security. As healthcare systems worldwide generate vast amounts of data, the challenge lies in harnessing this information without compromising confidentiality. Federated learning addresses this by allowing multiple institutions to collaborate on machine learning models without sharing sensitive data. In this context, the authors delve into the foundational principles of FL, illustrating how it enables the aggregation of decentralized data to improve diagnostic accuracy, develop personalized treatment plans, and enhance overall healthcare outcomes. The authors present real-world applications across various medical fields, from predictive analytics in chronic disease management to precision medicine and beyond. Additionally, the authors discuss the ethical and regulatory landscapes, providing insights into the challenges and solutions associated with implementing FL in healthcare. This book is designed for a diverse audience, including researchers, healthcare practitioners, data scientists, and policymakers. It aims to bridge the gap between cutting-edge technology and practical medical applications, offering a comprehensive guide to leveraging FL for healthcare innovation.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 244 pp. Englisch.…

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book features high-quality research papers presented at the International Conference on Deep Learning and Visual Artificial Intelligence (ICDLAI), held at Government Engineering College Bikaner, Bikaner, India, during March 16-17, 2024. The book pre.…

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book features high-quality research papers presented at the International Conference on Deep Learning and Visual Artificial Intelligence (ICDLAI), held at Government Engineering College Bikaner, Bikaner, India, during March 16-17, 2024. The book presents diverse range of topics, including advanced deep learning techniques, neural networks, image processing, object detection, and pattern recognition. 568 pp. Englisch. …

Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book features high-quality research papers presented at the International Conference on Deep Learning and Visual Artificial Intelligence (ICDLAI), held at Government Engineering College Bikaner, Bikaner, India, during March 16-17, 2024. The book presents diverse range of topics, including advanced deep learning techniques, neural networks, image processing, object detection, and pattern recognition. 568 pp. Englisch. …

Condición: New. Print on Demand.

Condición: New. PRINT ON DEMAND.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book features high-quality research papers presented at the International Conference on Deep Learning and Visual Artificial Intelligence (ICDLAI), held at Government Engineering College Bikaner, Bikaner, India, during March 16-17, 2024. The book presents diverse range of topics, including advanced deep learning techniques, neural networks, image processing, object detection, and pattern recognition.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 568 pp. Englisch. …

Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book features high-quality research papers presented at the International Conference on Deep Learning and Visual Artificial Intelligence (ICDLAI), held at Government Engineering College Bikaner, Bikaner, India, during March 16¿17, 2024. The book presents diverse range of topics, including advanced deep learning techniques, neural networks, image processing, object detection, and pattern recognition.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 568 pp. Englisch. …

Condición: New. Print on Demand.

Condición: New. PRINT ON DEMAND.