Intel, UPenn Form AI Initiative to Identify Brain Tumors via Secure Data


What You Should Know:

– To coincide with brain tumor awareness month in May, today Intel and the Perelman School of Medicine at the University of Pennsylvania (UPenn) announced an NIH-funded program that uses AI to identify brain tumors while protecting patient data.

– Funded by the National Institutes of Health, UPenn and these health care institutions will use Intel’s federated learning technology to produce a new AI model that is trained on the largest brain tumor dataset to date—all without sensitive patient data leaving the individual entities/hospitals. 

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.

What Is
Federated Learning?

Federated learning,  introduced by Google in 2017 , is a distributed
machine learning approach that enables multi-institutional collaboration on
deep learning projects without sharing patient data. In 2018, Intel began a
collaboration with the Center for Biomedical Image Computing and Analytics ( CBICA ) at the University
of Pennsylvania to show the first proof-of-concept application of federated
learning to real-world medical imaging

Federated Learning for Medical Imaging

Penn Medicine
and 29 healthcare and research institutions from the United States, Canada, the
United Kingdom, Germany, the Netherlands, Switzerland and India will use
federated learning, which is a distributed machine learning approach that
enables organizations to collaborate on deep learning projects without sharing
patient data.Penn Medicine and Intel Labs were the first to  publish a paper on
federated learning  in the medical imaging
domain, particularly demonstrating that the federated learning method could
train a model to over 99% of the accuracy of a model trained in the
traditional, non-private method. This paper was originally presented at the
International Conference on Medical Image Computing and Computer Assisted
Intervention (MICCAI) 2018 in Granada, Spain. The new work will leverage Intel
software and hardware to implement federated learning in a manner that provides
additional...

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