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3d ago

University of Utah Validates AI Toolkit Predicting Chronic Diseases with 85–99% Accuracy

RiskPath, an explainable AI tool, demonstrates unprecedented precision in identifying disease risk years before symptoms through advanced time-series algorithms.

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Overview

  • RiskPath, developed by University of Utah researchers, uses explainable AI to predict chronic and progressive diseases years before symptom onset.
  • The toolkit was validated across three large patient cohorts, successfully predicting eight conditions including depression, ADHD, and hypertension.
  • RiskPath achieves 85–99% predictive accuracy, a significant improvement over conventional systems that identify at-risk individuals with only 50–75% accuracy.
  • The system simplifies clinical implementation by requiring as few as 10 key health variables and provides visualizations to pinpoint critical intervention windows.
  • Ongoing research aims to integrate RiskPath into clinical decision support systems and expand its applicability to diverse populations and additional diseases.