AI gone astray: How subtle shifts in patient data send popular algorithms reeling, undermining patient safety By Casey Ross Data Analysis By Adam Yala, Janice Yang and Ludvig Karstens — Jameel Clinic, MIT Mike Reddy for STAT A novel investigation by STAT and the Massachusetts Institute of Technology found that subtle shifts in data fed into popular health care algorithms — used to warn caregivers of impending medical crises — can cause their accuracy to plummet over time, raising the prospect AI could do more harm than good in many hospitals. Read More |
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