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Federated Deep Learning for Healthcare: A Practical Guide with Challenges and Opportunities - Advances in Smart Healthcare Technologies
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Federated Deep Learning for Healthcare: A Practical Guide with Challenges and Opportunities - Advances in Smart Healthcare Technologies
This book provides a practical guide to federated deep learning for healthcare including fundamental concepts, framework, and the applications comprising of domain adaptation, model distillation, and transfer learning. It covers concerns in model fairness, data bias, regulatory compliance, and ethical dilemmas.
312 pages, 9 Tables, black and white; 41 Line drawings, black and white; 3 Halftones, black and whit
| Media | Books Hardcover Book (Book with hard spine and cover) |
| Released | October 2, 2024 |
| ISBN13 | 9781032689555 |
| Publishers | Taylor & Francis Ltd |
| Pages | 252 |
| Dimensions | 150 × 220 × 20 mm · 498 g |
| Language | English |
| Editor | Aung, Si Thu (Univ at Buffalo, USA) |
| Editor | Hassan, Md. Mehedi (Khulna Uni, Bangladesh) |
| Editor | Kaur, Amandeep (Chitkara University, India) |
| Editor | Kaushal, Chetna (Chitkara University, India) |
