Federated Learning for Internet of Medical Things

Federated Learning for Internet of Medical Things

Concepts, Paradigms, and Solutions

Bhattacharya, Pronaya; Tanwar, Sudeep; Verma, Ashwin

Taylor & Francis Ltd

11/2024

290

Mole

9781032300788

Pré-lançamento - envio 15 a 20 dias após a sua edição

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1. Potentials of Internet of Medical Things: Fundamentals and Challenges, 2. Artificial Intelligence Applications for IoMT, 3. Privacy and Security in Internet of Medical Things, 4. IoMT Implementation: Technological Overview for Healthcare Systems, 5. A New Method of 5G-Based Mobile Computing for IoMT Applications, 6. Trusted Federated Learning Solutions for Internet of Medical Things, 7. Early Prediction of Prevalent Diseases Using IoMT, 8. Trusted Federated Learning for Internet of Medical Things: Solutions and Challenges, 9. Security and Privacy Solutions for Healthcare Informatics, 10. IoT-Based Life-Saving Devices Equipped with Ambu Bags for SARS-CoV-2 Patients, 11. Security and Privacy in Federated Learning-Based Internet of Medical Things, 12. Use-Cases and Scenarios for Federated Learning Adoption in IoMT, 13. Blockchain for Internet of Medical Things
Healthcare Revolution;Cloud Computing;Blockchain;Artificial Intelligence;Federated Learning;IoMT;IoT Device;FL;Fog Computing;Blockchain Technology;Deep Learning Models;Smart Healthcare;Edge Computing;ECG Sensor;Smart Contract;Differential Privacy;Wearable Devices;Healthcare Data;Cryptographic Hash Function;PERS;SDN;Aggregation Server;Ambu Bag;Global Data Center;Stego Image;Tamil Nadu;Watermarked Signal;Watermark Embedder;Homomorphic Encryption;Arduino Ide