Intel Using Federated Learning to Preserve Privacy of Brain Tumor Training Data

The importance of such a method, is noted, and also the ability to use 'Federated learning'  to preserve the privacy of the large amount of data being used to train the method.  See Google's efforts on this at the tag below.

Intel Works with University of Pennsylvania in Using Privacy-Preserving AI to Identify Brain Tumors

Intel and the Perelman School of Medicine at the University of Pennsylvania are setting up a federation to train AI models that identify brain tumors.

Federated learning is a distributed machine learning approach that enables organizations to collaborate on machine learning projects without sharing sensitive data such as patient records. (Credit: Intel Corporation)

SANTA CLARA, Calif.--(BUSINESS WIRE)--What’s New: Intel Labs and the Perelman School of Medicine at the University of Pennsylvania (Penn Medicine) are co-developing technology to enable a federation of 29 international healthcare and research institutions led by Penn Medicine to train artificial intelligence (AI) models that identify brain tumors using a privacy-preserving technique called federated learning. Penn Medicine’s work is funded by the Informatics Technology for Cancer Research (ITCR) program of the National Cancer Institute (NCI) of the National Institutes of Health (NIH), through a three-year, $1.2 million grant awarded to principal investigator Dr. Spyridon Bakas at the Center for Biomedical Image Computing and Analytics (CBICA) of the University of Pennsylvania.

“AI shows great promise for the early detection of brain tumors, but it will require more data than any single medical center holds to reach its full potential. Using Intel software and hardware and support from some of Intel Labs' brightest minds, we are working with the University of Pennsylvania and a federation of 29 collaborating medical centers to advance the identification of brain tumors while protecting sensitive patient data.”

– Jason Martin, principal engineer, Intel Labs  .... '