Close Menu

    Subscribe to Updates

    Get the latest creative news from FooBar about art, design and business.

    What's Hot

    Hitman World of Assassination is coming to iOS and table tops

    2025 Acura ADX review: A crossover that balances budget with spirit

    Developers win Design Awards but have App Store complaints

    Facebook X (Twitter) Instagram
    Facebook X (Twitter) Instagram Pinterest VKontakte
    Sg Latest NewsSg Latest News
    • Home
    • Politics
    • Business
    • Technology
    • Entertainment
    • Health
    • Sports
    Sg Latest NewsSg Latest News
    Home»Health»University of Utah Researchers Develop Explainable AI Toolkit to Predict Disease Before Symptoms Appear
    Health

    University of Utah Researchers Develop Explainable AI Toolkit to Predict Disease Before Symptoms Appear

    AdminBy AdminNo Comments4 Mins Read
    Facebook Twitter Pinterest LinkedIn Tumblr Email
    Share
    Facebook Twitter LinkedIn Pinterest Email


    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:

    • Enhanced Understanding of Disease Progression: RiskPath can map how different risk factors change in importance over time, revealing critical windows for intervention. For example, the study showed how screen time and executive function become increasingly important risk contributors for ADHD as children approach adolescence.
    • Streamlined Risk Assessment: Though RiskPath can analyze hundreds of health variables, researchers found that most conditions can be predicted with similar accuracy using just 10 key factors, making implementation more feasible in clinical settings.
    • Practical Risk Visualization: The system provides intuitive visualizations showing which time periods in a person’s life contribute most to disease risk, helping researchers identify optimal times for preventive interventions.

    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

    Share. Facebook Twitter Pinterest LinkedIn Tumblr Email
    Admin
    • Website

    Related Posts

    Victoria’s Voice Foundation Marks National Naloxone Awareness Day on June 6 with Special Event on Capitol Hill

    Bowled over for breakfast cereal

    Premier Primary Care to Celebrate Grand Opening in Urbana, MD with Ribbon Cutting and Community Open House

    Clearing the air on e-cigarettes

    Add A Comment
    Leave A Reply Cancel Reply

    Editors Picks

    Microsoft’s Singapore office neither confirms nor denies local layoffs following global job cuts announcement

    Google reveals “material 3 expressive” design – Research Snipers

    Trump’s fast-tracked deal for a copper mine heightens existential fight for Apache

    Top Reviews
    9.1

    Review: Mi 10 Mobile with Qualcomm Snapdragon 870 Mobile Platform

    By Admin
    8.9

    Comparison of Mobile Phone Providers: 4G Connectivity & Speed

    By Admin
    8.9

    Which LED Lights for Nail Salon Safe? Comparison of Major Brands

    By Admin
    Sg Latest News
    Facebook X (Twitter) Instagram Pinterest Vimeo YouTube
    • Get In Touch
    © 2025 SglatestNews. All rights reserved.

    Type above and press Enter to search. Press Esc to cancel.