Web: http://arxiv.org/abs/2208.03392

Aug. 16, 2022, 1:14 a.m. | Ashish Rauniyar, Desta Haileselassie Hagos, Debesh Jha, Jan Erik Håkegård, Ulas Bagci, Danda B. Rawat, Vladimir Vlassov

cs.CV updates on arXiv.org arxiv.org

With the advent of the IoT, AI, and ML/DL algorithms, the data-driven medical
application has emerged as a promising tool for designing reliable and scalable
diagnostic and prognostic models from medical data. This has attracted a great
deal of attention from academia to industry in recent years. This has
undoubtedly improved the quality of healthcare delivery. However, these
AI-based medical applications still have poor adoption due to their
difficulties in satisfying strict security, privacy, and quality of service
standards (such …

applications arxiv challenges federated learning future learning lg medical research taxonomy trends

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