Could Utah’s RiskPath AI stop chronic disease before symptoms even start?

University of Utah researchers have unveiled RiskPath, an explainable-AI platform that sifts through years of electronic-health-record data to flag individuals at high risk for conditions like heart disease, diabetes and depression long before they feel ill. Lead scientist Dr. Nina de Lacey says the goal is to “identify people at risk before they get ill” so doctors can intervene early and even prevent serious mental-health crises in a state grappling with a suicide epidemic. KUTV

Chief AI Officer Dr. Manish Parashar hails the technology’s life-saving potential but warns that over-reliance on opaque models can be dangerous; RiskPath’s XAI design lets clinicians trace exactly how each prediction was generated. The team now urges regulators to craft FDA-style rules for medical AI, envisioning a future where a patient’s record quietly pings their doctor with a heads-up long before disease reaches the “red zone.” KUTV