A scalable federated learning solution for secondary care using low-cost microcomputing: privacy-preserving development and evaluation of a COVID-19 screening test in UK hospitals

A scalable federated learning solution for secondary care using low-cost microcomputing: privacy-preserving development and evaluation of a COVID-19 screening test in UK hospitals

<p><b>Background</b></p> Multicentre training could reduce biases in medical artificial intelligence (AI); however, ethical, legal, and technical considerations can constrain the ability of hospitals to share data. Federated learning enables institutions to participate in alg...

書誌詳細
主要な著者:	Soltan, AS, Thakur, A, Yang, J, Chauhan, A, D'Cruz, LG, Dickson, P, Soltan, MA, Thickett, DR, Eyre, DW, Zhu, T, Clifton, DA
フォーマット:	Journal article
言語:	English
出版事項:	Elsevier 2024

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