SALT LAKE CITY - Researchers at the University of Utah's Department of Psychiatry and Huntsman Mental Health Institute have introduced RiskPath, an open source software toolkit that uses Explainable Artificial Intelligence (XAI), to predict whether individuals will develop progressive and chronic diseases years before symptoms appear, potentially transforming how preventive healthcare is delivered. XAI is an artificial intelligence system that can explain complex decisions in ways humans can understand.
The new technology represents a significant advancement in disease prediction and prevention by analyzing patterns in health data collected over multiple years to identify at-risk individuals with unprecedented accuracy of 85-99%. Current medical prediction systems for longitudinal data often miss the mark, correctly identifying at-risk patients only about half to three-quarters of the time. RiskPath uses advanced timeseries AI algorithms and makes them explainable in order to deliver comprehensive models that provide crucial insights into how risk factors interact and change in importance throughout the disease development process.
Lead researcher Nina de Lacy, MD said, "Chronic, progressive diseases account for over 90% of healthcare costs and mortality. By identifying high-risk individuals before symptoms appear or early in the disease course and pinpointing which risk factors matter most at different life stages, we can develop more targeted and effective preventive strategies. Preventative healthcare is perhaps the most important aspect of healthcare right now, rather than only treating issues after they materialize."
The research team validated RiskPath across three major long-term patient cohorts involving thousands of participants to successfully predict eight different conditions, including depression, anxiety, ADHD, hypertension, and metabolic syndrome.
The research team is now exploring how RiskPath could be integrated into clinical decision support systems, preventive care programs, and the neural underpinnings of mental illness. They plan to expand their research to include additional diseases and diverse populations.
