The ability to inexpensively predict events such as stroke and heart attack is something of a holy grail for cardiologists, and a new study presented at this year’s annual meeting of the Radiological Society of North American (RSNA) provides just that capability. A study of an algorithm developed to examine a single chest X-ray suggests that the data generated by the algorithm can be as effective in establishing the patient’s risk of these events as a standard approach that relies on information that isn’t always readily available to the clinician.
A number of entities have sounded off on the FDA’s discussion paper for artificial intelligence (AI), including several medical societies that would like to see autonomously operating algorithms subjected to more stringent review than supervised algorithms. Vibhor Rastogi, general partner at Symphony AI of Los Altos, Calif., told BioWorld that the company is on board with many of these concerns, adding that the FDA discussion paper does a “good job of balancing innovation and patient safety.”
The comment period has closed on the U.S. FDA’s discussion draft for artificial intelligence (AI) in medical devices, a paper that attracted the attention of medical societies and regulated industry. One of the questions posed by industry was whether the FDA is in a position to deal with the massive volumes of data developers would have to disclose to the agency, creating concern that such disclosures would amount to little more than an obligatory and useless data dump.
