Federated Learning for Neural Disorders in Healthcare 6.0
暫譯: 醫療領域神經疾病的聯邦學習 6.0
Reddy C., Kishor Kumar, Nag, Anindya
- 出版商: CRC
- 出版日期: 2025-05-14
- 售價: $7,370
- 貴賓價: 9.5 折 $7,002
- 語言: 英文
- 頁數: 396
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 1032968877
- ISBN-13: 9781032968872
尚未上市，無法訂購
商品描述
This reference text offers a relevant and thorough examination of the overlap between neuroscience and federated learning. It explores the complexities of utilizing federated learning algorithms for MRI data analysis, demonstrating how to improve the accuracy and efficiency of diagnostic procedures. The book covers topics such as the prediction and diagnosis of Alzheimer's disease using neural networks and ensuring data privacy and security in federated learning for neural disorders.
This book:- Provides a thorough examination of the transformative impact of federated learning on the diagnosis, treatment, and understanding of brain disorders.
- Focuses on combining federated learning with magnetic resonance imaging (MRI) data, which is a fundamental aspect of contemporary neuroimaging research.
- Examines the use of federated learning as a promising approach for collaborative data analysis in healthcare, with a focus on maintaining privacy and security.
- Explores the cutting-edge field of healthcare innovation by examining the interface of neuroscience and machine learning, with a specific focus on the breakthrough technique of federated learning.
- Offers a comprehensive understanding of how federated learning may transform patient care, covering both theoretical ideas and practical examples.
It is primarily written for graduate students and academic researchers in electrical engineering, electronics, and communication engineering, computer science and engineering, and biomedical engineering.
商品描述(中文翻譯)
這本參考書提供了神經科學與聯邦學習之間重疊的相關且深入的探討。它探討了利用聯邦學習演算法進行MRI數據分析的複雜性，展示了如何提高診斷程序的準確性和效率。本書涵蓋了使用神經網絡預測和診斷阿茲海默症，以及在神經疾病的聯邦學習中確保數據隱私和安全等主題。
本書：
- 徹底檢視聯邦學習對於腦部疾病的診斷、治療和理解所帶來的變革性影響。
- 專注於將聯邦學習與磁共振成像（MRI）數據結合，這是當代神經影像研究的基本面向。
- 檢視聯邦學習作為醫療保健中協作數據分析的有前景方法，重點在於維護隱私和安全。
- 通過檢視神經科學與機器學習的交界，探索醫療保健創新的前沿領域，特別關注聯邦學習這一突破性技術。
- 提供對聯邦學習如何改變病人護理的全面理解，涵蓋理論概念和實際範例。
本書主要為電機工程、電子學、通信工程、計算機科學與工程以及生物醫學工程的研究生和學術研究人員所撰寫。
作者簡介
Kishor Kumar Reddy C is currently working as an associate professor in the Department of Computer Science and Engineering, Stanley College of Engineering and Technology for Women, Hyderabad, India. He has research and teaching experience of more than 13 years. He has published more than 90 research papers in national and international conferences, book chapters, and journals indexed by SCIE, Scopus and others. He has authored two textbooks and 12 edited books. He is a member of ISTE, CSI, IAENG, UACEE, and IACSIT.
Anindya Nag obtained an M.Sc. in Computer Science and Engineering from Khulna University in Khulna, Bangladesh, and a B.Tech. in Computer Science and Engineering from Adamas University in Kolkata, India. He is currently a lecturer in the Department of Computer Science and Engineering at the Northern University of Business and Technology in Khulna, Bangladesh. His research focuses on health informatics, medical Internet of Things, neuroscience, and machine learning. He serves as a reviewer for numerous prestigious journals and international conferences. He has authored and co-authored around 32 publications, including journal articles, conference papers, book chapters, and has co-edited five books.
作者簡介(中文翻譯)
Kishor Kumar Reddy C 目前擔任印度海得拉巴斯坦利女子工程技術學院計算機科學與工程系的副教授。他擁有超過13年的研究和教學經驗。他在國內外會議、書籍章節以及被SCIE、Scopus等索引的期刊上發表了超過90篇研究論文。他是兩本教科書的作者和12本編輯書籍的編輯。他是ISTE、CSI、IAENG、UACEE和IACSIT的成員。
Anindya Nag 於孟加拉國庫爾納大學獲得計算機科學與工程碩士學位，並於印度加爾各答的阿達馬斯大學獲得計算機科學與工程學士學位。他目前是孟加拉國庫爾納北方商業與技術大學計算機科學與工程系的講師。他的研究重點包括健康資訊學、醫療物聯網、神經科學和機器學習。他擔任多本知名期刊和國際會議的審稿人。他已發表和共同發表約32篇出版物，包括期刊文章、會議論文、書籍章節，並共同編輯了五本書籍。
