If the promise of adaptive artificial intelligence (sometimes called machine learning) is to be achieved in the medical area, the U.S. Food and Drug Administration's regulation of medical devices is going to have to graduate from geometry to calculus. By its nature, machine learning changes the details of its output constantly.
The rigid regulatory model requiring FDA preapproval of all “major changes” (defined as anything that could affect product safety or effectiveness) that has served the FDA, and the public health, well for many years cannot handle adaptive artificial intelligence. The fundamental insight of the calculus was that it allowed measurement of rates of change rather than change itself.
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