Study co-author Rivka Colen, MD, an associate professor of Radiology at the University of Pittsburgh School of Medicine, said that this paper and the larger federated learning project open up possibilities for even more uses of Artificial Intelligence in health care.
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“I think it’s a huge game changer,” Colen said. “Radiomics is to radiology what genomics was to pathology. AI will revolutionize this field, because, right now, as a radiologist, most of what we do is descriptive. With deep learning, we’re able to extract information that is hidden in this layer of digitized images.”
Additional authors on this paper include: Micah J Sheller, Brandon Edwards G Anthony Reina, Jason Martin, Aikaterini Kotrotsou, Mikhail Milchenko, Weilin Xu, and Daniel Marcus.
This research was partly supported by the National Institutes of Health (NIH) under award numbers NCI:U01CA242871, NINDS:R01NS042645, NCI:U24CA189523 NCI:U24CA204854, and UPMC CCSG P30 CA047904.
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