Latest news with #One-UResponsibleAIInitiative
Yahoo
19-05-2025
- Health
- Yahoo
U. researchers unveil AI-powered tool for disease prediction with ‘unprecedented accuracy'
It's long been a goal in medicine to better understand the long trajectories of diseases in hopes of engaging in better prevention and early intervention. 'Collectively, they're (chronic and progressive diseases) responsible for about 90% of the health care costs in this country and the vast majority of morbidity and mortality,' said Nina de Lacy, a professor of psychiatry and member of the One-U Responsible AI Initiative's executive committee. Now, University of Utah researchers have taken a crucial step in doing so, unveiling a new, open-source software tool kit that uses artificial intelligence to predict whether individuals will develop progressive and chronic diseases years before symptoms appear. Enter RiskPath, a new technology that analyzes patterns in health data collected over multiple years to identify at-risk individuals with 'unprecedented accuracy' of 85% to 99%, according to National Institute of Mental Health-sponsored research published last week by the U.'s Department of Psychiatry and Huntsman Mental Health Institute. The program harnesses explainable AI, which is designed to explain complex decisions in ways humans can understand. 'Explainability means, can I explain enough about how AI accomplished this prediction such that it becomes understandable to humans?' de Lacy said. 'That would be things like what RiskPath does.' De Lacy explained something that has always been a challenge in biomedicine is building models and analyzing longitudinal data, meaning it's collected over many time periods. 'One of the major use cases in using longitudinal data is course development, understanding how people grow up and develop over time,' de Lacy said. 'And one of the other ones is what RiskPath is aimed at, which is understanding progressive or chronic disease. There are many progressive and chronic diseases out there, and some of the big ones are things that are the major diseases that affect humans.' The research shows 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. Unlike existing prediction systems for longitudinal data, RiskPath uses advanced time-series AI algorithms that deliver crucial insights into how risk factors interact and change in importance throughout the disease process. '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 health care is perhaps the most important aspect of health care right now, rather than only treating issues after they materialize,' de Lacy said. De Lacy and the rest of 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. While RiskPath is primarily a research tool to help researchers build better risk stratification models, de Lacy hopes it will eventually be used in a health care setting to improve disease management. 'Some may be using that to build models that can be implemented in health care, and we kind of hope that they do that. But ... a big part of what my lab is interested in doing is building tools that do a better job of risk stratification. We're very interested in prevention,' de Lacy said. 'The ultimate aim of RiskPath and tools like RiskPath is to help people build better risk stratification tools and decision support tools. 'And what those do is help clinicians, and maybe one day patients, be able to understand their risk for a chronic or progressive disease better and earlier,' she said.
Yahoo
12-02-2025
- Business
- Yahoo
Opinion: Utah is working toward responsible AI leadership. Join us
Last week, President Donald Trump said Chinese startup DeepSeek's successful launch of its latest AI model 'should be a wake-up call' for American industry. As the U.S. hustles to maintain its leadership in artificial intelligence, our long-term strategy needs to involve breaking down silos and working across sectors to provide the supporting cyber infrastructure, education and policies that can drive innovation. Leadership at a national scale won't be achieved by one company, whether it's OpenAI or DeepSeek — it needs partnerships that can effectively bring together industry, academia and government. The most successful country (or state) will be the one that builds an innovation ecosystem spanning these sectors where AI can flourish, where the best minds can come together to advance AI and address important issues — for instance, improving medical diagnoses and treatments, more effectively predicting wildfires, or counteracting the downward trend of children's reading skills. In Utah, we're working to catalyze such an ecosystem. On Jan. 28, about 70 people joined us at a Utah Tech Week event launching Utah's Responsible AI Community Consortium. Representatives from academia, government and businesses large and small — from Nvidia and Amazon Web Services to local startups — discussed how we can all work together to advance AI in Utah. At the University of Utah, this work started under the umbrella of the $100 million One-U Responsible AI Initiative, launched by university President Taylor Randall in October 2023. We're responsibly accelerating impactful AI research at the University of Utah, but we recognize the need to work across the state to maximize our impact. We want to leverage other AI efforts, both public and private, and create a movement where the whole is greater than the sum of its parts. We want a system where anyone across the state can learn about, contribute to and benefit from AI. So last fall, we started four community-led responsible AI special interest groups: policy, infrastructure, frameworks and best practices, and workforce development and education. The work of those groups will funnel into a consortium to benefit all stakeholders. While the University of Utah is facilitating this effort, the consortium is a co-op led by its members. We encourage all interested Utahns to join us and make their voices heard in this formative stage. One of our community consortium's founding members is Zachary Boyd, director of Utah's Office of AI Policy. At our Jan. 28 event, Boyd described the consortium as a way to synthesize Utah's expertise and form partnerships as we work toward shared goals. 'Everything we want to do — from building responsible AI norms to making sure that adoption of AI technology throughout all sectors goes as smoothly as possible — the basis of all of that is the networks of connection,' Boyd said. One example of a cross-sector network with the potential to benefit all Utahns: public-private partnerships where businesses work with educational institutions to build training programs that develop students' and workers' AI skills. We're already working toward such partnerships, and they'll be critical to our success. As Kevin Williams — Ascend AI Labs founder and co-leader of our workforce development and education special interest group — so incisively said at our Jan. 28 event, 'At the end of the day, all of the infrastructure, all of the policy, all of the frameworks end up at the pointy end of the spear, which is the people and the work.' From providing computing power to developing an AI-ready workforce, it will take a village to make Utah a leader in AI. Our community consortium is that village. During Utah Tech Week, Bassam Salem — a founding member of the consortium, a member of the University of Utah Board of Trustees and the founder of Mindshare Ventures — pointed out Utah's advantage lies in its culture. 'This is not normal,' Salem told the crowd on Jan. 28. 'It's not normal for a university to invest $100 million in support of a societally impactful initiative so quickly and to make it so open, transparent and for the benefit of the entire community. It's not normal for a state government to be so accessible, so involved and so engaged with industry. And what I really love about Utah and the Utah tech scene is it's not normal that we're so collaborative, so cooperative and so constructive as an industry, all helping one another.' Salt Lake City will once again host the Winter Olympics in 2034, Salem reminded us. 'Wouldn't it be great if in the next nine years we can make this materialize?' he asked. 'We can make Utah a hub of responsible AI.' Join us.
