Federated Learning for Healthcare

R. Anandan completed his UG, PG, Doctorate in Computer Science and Engineering and Post-Doctoral Degree - D.Sc. in Computer Science and Engineering from Mexico in North America.He is IBMS/390 Mainframe professional and he is recognized as Chartered Engineer from Institution of Engineers in India and received fellowship from Bose Science Society, India. He completed 7 certification courses mainly from CISCO. He is currently working as Professor, Department of Computer Science and Engineering, School of Engineering and Director – Innovation and Incubation, Vels Institute of Science, Technology & Advanced Studies (VISTAS), Chennai, Tamil Nadu, India which is Pioneer Institution in Engineering. He has vast experience in corporate and all levels of Academic in Computer Science and Engineering his knowledge of interests not limited to Artificial intelligence Soft Computing, Machine Learning, High Performance Computing, Big data Analytics, Image Processing, 3D printing and knowledge Engineering. Under his eminent guidance 8 Ph.D Research Scholars are pursuing, under his Supervision. 11 Ph.D., Research Scholars have been awarded under his Guidance and Supervision. He associated as Member in many reputed International and National societies like International Association of Engineers (IAENG) Hong Kong, Computer Science Teacher Association (CSTA) New York, Universal Association of Computer and Electronics Engineers, USA, Association of Computer Sciences and Information Technology (IACSIT), Singapore, Institution of Engineers, India, Computer Society of India and Indian Society of Technical Education (I.S.T.E). He serves as Editorial Board Member / Technical Committee/ Reviewer of International Journal such Arab/UK/USA journals. He servers as International Committee Members towards International Conference conducted in association with Springer and Scopus.He has published more than 135 research papers in various International Journals such in Scopus, SCI and referred journal. He has presented 90 papers at various International Conferences. He received 20 awards from National and Inter-National Agencies He authored and Edited 26 books which includes 10 International Books and published 30 chapters in various International Books. He filed 20 patents of his work and 1 International and 3 Indian Patent granted. He received grant for his Project sanctioned by AICTE under Research Promotion Scheme for the year 2021-2022 and MSME Idea Hackathon 2022 for the year 2021-2022 also received 3 project grants from the private organization. He done Consultancy Projects for some of the reputed organization and also associated as Knowledge Partner in leading Software Company.Souvik Pal is a Professor in the Department of Computer Science and Engineering at Sister Nivedita University (Techno India Group), Kolkata, India. He holds M.Tech and Ph.D. degrees in Computer Science and Engineering from KIIT University, Bhubaneswar, and brings over a decade of academic and research experience to his role. Prior to joining Sister Nivedita University, Dr. Pal held academic positions at several esteemed institutions, including Global Institute of Management and Technology; Brainware University, Kolkata; JIS College of Engineering, Nadia; Elitte College of Engineering, Kolkata; and Nalanda Institute of Technology, Bhubaneswar.Dr. Pal is the author or editor of more than 25 books published by leading international and he holds three patents. He currently serves as Series Editor for several notable book series, including Advances in Learning Analytics for Intelligent Cloud-IoT System, Internet of Things: Data-Centric Intelligent Computing, Informatics, and Communication (CRC Press, Taylor & Francis Group), and Conference Proceedings Series on Intelligent Systems, Data Engineering, and Optimization (CRC Press, Taylor & Francis Group). A prolific researcher, Dr. Pal has published extensively in Scopus-indexed, SCI, and SCIE journals and international conferences. He has served as the Organizing Chair for RICE 2019 and RICE 2020 (Vietnam), and ICICIT 2019 (Tunisia), and has delivered keynote addresses at ICICCT 2019 (Turkey) and ICTIDS 2019, 2021 (Malaysia). He has also contributed as Proceedings Editor for several international conferences. His professional contributions include serving as Associate Editor, Guest Editor, and Editorial Board Member for over 100 reputed international journals and conferences. Dr. Pal’s research interests include cloud computing, big data, the Internet of Things (IoT), wireless sensor networks, and data analytics. He is an active member of numerous professional organizations, including IEEE, CSI, CSTA/ACM (USA), IAENG (Hong Kong), IRED (USA), MACEEE (India), IACSIT (Singapore), and MAASCIT (USA).D. Balaganesh, Vice Dean of Computer Science and Informatics at the Berlin School of Business and Innovation, Germany. With 23 years of professional teaching experience spanning multiple countries including India, Oman, Malaysia, and Germany, Professor Balaganesh is a seasoned academic with a deep expertise in Information Technology and the latest wireless fidelity innovations. His research interests are focused on Data Science, AI, malware detection, web mining, and open-source technology.As Vice Dean of Computer Science and Informatics, Professor Balaganesh has delivered comprehensive training in mobile applications, open-source ERP, software testing, and MySQL. He has developed significant software applications such as "Timetable Automation" and "Online Exam," and has also authored and edited numerous books and book chapters. His ability to elucidate complex technical concepts in a clear and precise manner is widely recognized. Actively involved in several professional bodies, Professor Balaganesh is an elected member of the Michigan Association for Computer Users in Learning (MACUL) in the USA, a member of the International Association of Engineers (IAENG) in Hong Kong, a member of the Institute for Engineering Research and Publication (IFERP), and a member of the Computer Science Teacher Association (CSTA) in New York. He serves on editorial boards, technical committees, and as a reviewer for numerous international journals from regions such as the Arab world, Poland, Europe, and the USA.He is a key editor of the book "Intelligent Computing and Innovation on Data Science: Lecture Notes in Networks and Systems" and has edited two notable book chapters: "Internet-of-Robotic-Things and Ubiquitous Computing" and "The Internet of Medical Things (IoMT): Healthcare Transformation”.ORCiD: https://orcid.org/0000-0003-3771-3795Farshad Badie holds a PhD (earned from Aalborg University in Denmark) in Human-Centered Communication & Informatics, specializing in logic, information science, and learning/cognitive science within socio-technical communication/interaction systems. Dr. Badie’s research primarily focuses on conceptual/logical languages and their applications in semantic knowledge modelling. Specifically, his research frameworks involve the logical, ontological, and semantic analysis of the fundamental components of meaning and cognition within cognitive/knowledge agents’ interactions. Furthermore, he analytically explores the conceptual and logical aspects of change and innovation in human-centered and organisational contexts, considering both systematic and strategic viewpoints. Dr. Badie has a high record of publications in well-known journals, conference proceedings, and book series. Additionally, he serves as an editorial board member and reviewer for numerous journals. He has also participated as an organising and scientific committee member in over 170 conferences and workshops held across Europe, America, Australia, Asia, and Africa.ORCiD: https://orcid.org/0000-0003-1534-3332

• Chapter 1 Framework of Federated Learning and Implementation Through Internet of Things Chapter 2 Federated Learning for Internet of Things Chapter 3 Enhancing Federated Learning in Healthcare Using Adaptive Genetic Model Aggregation Chapter 4 Energy Efficiency Iot Devices in Healthcare Field Using FederatedLearning Chapter 5 Artificial Intelligence in Mental Health: Innovation, Ethics, and Privacy via Federated Learning Chapter 6 Adaptive Energy Management in Healthcare IoT Devices Using Federated Intelligence Chapter 7 Artificial Intelligence Based Federated Learning in Healthcare Chapter 8 Federated Learning for Diabetic Retinopathy: Enhancing Detection with Data Privacy Chapter 9 Federated Learning Framework for Motif Structure Prediction Chapter 10 Cyber Threat Detection in IoT-Enabled Edge Computing Using Optimized Federated Deep Learning Chapter 11 Optimized Migraine Detection in Healthcare: Exploring RandomForest and XGBoost with Prospects for Federated Learning Chapter 12 Unlocking the Knowledge of Patient Similarities in Chronic Kidney Disease Using Machine Learning with Prospects of Federal Learning Chapter 13 Dynamic Pricing for Revenue Management in Health and Hospitality Industry with Federated Learning Chapter 14 Federated Learning for Real-Time Disease Prediction: A Scalable Framework for Personalized Healthcare in Internet of Things-enabled Environment