University of Utah Unveils AI Toolkit for Early Disease Prediction
Researchers at the University of Utah have introduced a new AI toolkit named RiskPath, designed to predict chronic diseases before symptoms appear, announced in a press release. Developed by the Department of Psychiatry and the Huntsman Mental Health Institute, RiskPath uses Explainable Artificial Intelligence (XAI) to analyze health data and identify at-risk individuals with an accuracy of 85-99%.
RiskPath represents a significant advancement in disease prediction by utilizing advanced timeseries AI algorithms. These algorithms provide insights into how risk factors interact and change over time, allowing for more targeted preventive strategies. The toolkit has been validated across three major long-term patient cohorts, successfully predicting conditions such as depression, anxiety, ADHD, hypertension, and metabolic syndrome.
The research team is exploring how RiskPath can be integrated into clinical decision support systems and preventive care programs. They aim to expand their research to include additional diseases and diverse populations, potentially transforming preventive healthcare delivery.
We hope you enjoyed this article
Consider subscribing to one of our newsletters like Life AI Weekly or Daily AI Brief.
Also, consider following us on social media:
More from Life Sciences
Sep 20 IDC Names ZS a Leader in Life Sciences Evidence Services Sep 20 Brainomix Selected for UK Future Fifty Programme Sep 19 Rutgers and RWJBarnabas Health Launch AWS Health Innovation Hub Sep 19 Vetology Rebuilds 94 Veterinary Radiology AI Classifiers Sep 19 NAVER D2SF Backs ImpriMed in $10 Million Bridge RoundLife AI Weekly
Weekly coverage of AI applications in healthcare, drug development, biotechnology research, and genomics breakthroughs.
Industry analysis
2025 Global Business Services Agenda: Gen AI Takes Center Stage
This industry analysis by The Hackett Group explores the transformative impact of generative artificial intelligence (Gen AI) on global business services (GBS) in 2025. The study highlights the shift from exploration to acceleration of Gen AI initiatives, with 89% of executives advancing these projects to improve customer satisfaction, innovate products, and reduce costs. The report also discusses the challenges and strategies for successful Gen AI adoption, emphasizing the need for a technology-enabled operating model and the importance of reskilling the workforce.
Read moreYou may also like
Atman Health Wins ARPA-H Award to Build Heart Failure AI
ARPA-H Awards UpDoc Up to $9.2 Million for Clinical AI
NYU Langone AI Uses Multiple 3D Mammograms to Predict Breast Cancer Risk
Probably Genetic Gets Up to $10M ARPA-H Contract for Rare Disease AI
UT Medical and TransformativeMed Build Agentic AI Discharge Planning Tool
Daily AI Brief: the AI news that matters, in your inbox.