Health IT Analytics March 8, 2021
An artificial intelligence method can help researchers collaboratively train algorithms without compromising patient data privacy.
A new approach could help researchers build high-quality artificial intelligence algorithms while protecting patient data privacy, accelerating model development and innovation, according to a study published in Nature Communications.
A major challenge of developing successful AI algorithms is the availability of data and patient privacy, researchers noted. Sharing medical data, even if the information is de-identified, can pose some risk to the privacy of patients.
Recently, researchers have explored an alternative method of training AI algorithms that avoids direct data sharing. Called federated learning, the approach involves using data from a variety of institutions and distributing computational training operations across all sites.
“In federated learning,...
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