SALT LAKE CITY, April 29, 2025 /PRNewswire/ — Researchers at the University of Utah’s Department of Psychiatry and Huntsman Mental Health Institute today published a paper introducing 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.
“Chronic, progressive diseases account for over 90% of healthcare costs and mortality,” said lead researcher Nina de Lacy, MD. “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 technology offers several key advantages:
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.
The full study on RiskPath was published in the April issue of CellPress Patterns, and can be found here. The research was led by Nina de Lacy, Michael Ramshaw, and Wai Yin Lam from the Department of Psychiatry at the University of Utah. De Lacy serves on the One-U Responsible AI Initiative Executive Committee. The work was supported by the National Institute of Mental Health.
About Huntsman Mental Health Institute
Huntsman Mental Health Institute at the University of Utah is a first-of-its-kind model created to address one of our nation’s greatest challenges: mental health and substance use disorders. The institute combines the strength of one of America’s leading research universities with the nation’s best integrated mental health crisis care model and a comprehensive continuum of care that includes a 161-bed hospital and more than 85 outpatient locations. We educate hundreds of learners every year and provide both unique and wide-ranging educational opportunities in psychiatry and mental health. Our innovative approach to research uses “teams of teams” to bring together different disciplines to uncover new ways to tackle complex problems. A gift of $150 million from the Huntsman family helps power our mission to advance mental health knowledge, hope, and healing for all.
SOURCE Huntsman Mental Health Institute
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