Researchers at the University of Pennsylvania's Perelman School of Medicine, in conjunction with the University of Texas MD Anderson Cancer Center, Washington University, and the Hillman Cancer Center at the University of Pittsburgh, have developed a machine learning method that can facilitate the sharing of patient data without compromising privacy.
The model uses the federated learning approach that trains an algorithm across multiple decentralized devices or servers containing local data samples without exchanging them.
The researchers found the approach to be successful in analyzing magnetic resonance imaging (MRI) scans and distinguishing between healthy brain tissue and cancerous regions.
The model could allow doctors in hospitals worldwide to input their own patient brain scans, which would support the development of a concensus model that would be clinically useful.
From Penn Medicine News
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