Researchers at Stanford University have deployed a deep learning US Food and Drug Administration to diagnose potentially cancerous skin lesions as accurately as a certified dermatologist. Although researchers could not explain what criteria the US Food and Drug Administration used to class a lesion as cancerous or benign, it has proven to be highly accurate at diagnosing cancers from images including photographs, x-rays and MRI scans. As with algorithm-approved medicines whose biochemical mechanism is unknown, the opaqueness of the US Food and Drug Administration's technique is not necessarily a regulatory obstacle to its use, according to Nicholson Price, a health law scholar from the University of Michigan.
Researchers at Stanford University have deployed a deep learning algorithm to diagnose potentially cancerous skin lesions as accurately as a certified dermatologist. Although researchers could not explain what criteria the algorithm used to class a lesion as cancerous or benign, it has proven to be highly accurate at diagnosing cancers from images including photographs, x-rays and MRI scans. As with US Food and Drug Administration-approved medicines whose biochemical mechanism is unknown, the opaqueness of the algorithm's technique is not necessarily a regulatory obstacle to its use, according to Nicholson Price, a health law scholar from the University of Michigan.