Artificial intelligence (AI) and automation are enabling researchers to advance discoveries into patient care faster and with greater precision, opening new ways to address complex needs in medicine.

"With AI, they're now able to ask and answer questions that they were not able to answer before," says Cui Tao, Ph.D., a professor of Biomedical Informatics and the Nancy Peretsman and Robert Scully Chair of Artificial Intelligence and Informatics at Mayo Clinic.  

Researchers are also using AI to identify clinical trials for patients and to accelerate the research process — from early ideas to new treatments in patient care.   

Watch: Dr. Cui Tao explains how researchers are using AI tools to accelerate their work

Journalists: Broadcast-quality soundbites are available for downloads at the end of the post. Please courtesy: "Mayo Clinic News Network." 

Using AI to accelerate cures  

Dr. Cui Tao shares her perspective on how researchers are using AI to reshape scientific discovery and accelerate the path to patient care: 

What does it mean to use AI to accelerate research?  
Using AI to accelerate research discovery is more than just using AI as a downstream analytics tool. It's about being able to embed AI into the whole procedure.  

Traditionally, when we conduct research, it's more of a linear procedure — from hypothesis generation to study design to collecting data and, finally, getting the result and interpreting the result. That's a linear process. But with AI, we're able to accelerate the whole process and iteratively test each step at the same time. 

How does using AI change the way studies and clinical trials are designed?
We can actually develop different AI agents for cohort matching, for clinical design, to refine how we conduct clinical trials in the traditional way.  

Our teams can also use AI to help patients understand the complex informed consent forms and to help identify those patients who are likely to be eligible for certain trials, from recruiting to data analysis to long-term follow-up. 

What do researchers tell you excites them most about these approaches? 
With AI, now we're able to accelerate everything, so it actually saves critical time for our researchers so that they can focus more fully on innovation, creativity and research.  

How is Mayo Clinic ensuring discovery is focused on the right things for patients?  
Whatever AI tools we design, they need to fulfill the needs of our patients and clinicians. We also emphasize AI regulation — the AI tools need to be safe, need to be trustworthy, before we can put them into actual patient care. 

Why is a multidisciplinary approach across biomedical, computational and social sciences important? From physicians to clinicians to data scientists to AI scientists and engineers ... We need to all work together to make sure that whatever we're building is impactful.  

And we need to ensure a bidirectional translational path: First, we need to be able to understand the clinical or biomedical question and translate that into an AI problem; and second, we need to be able to translate the AI solutions back into practice so that people can use them. 

Join leading experts at Mayo Clinic's AI Research Summit 

Join Dr. Tao and other experts at Mayo Clinic's AI Research Summit on June 4–5 in Rochester, Minnesota, and online. This conference brings together leaders and innovators to share advances in healthcare AI research, explore emerging methods and build collaborations.  

This year's summit will explore topics such as multi-agent clinical intelligence, simulation, virtual twins and multimodal foundation models. Sessions will also focus on translating AI research into clinical practice and building trustworthy, governable systems. 

In addition to Dr. Tao, the keynote speakers are:  

• Peter Lee, Ph.D., president of Microsoft Research and Mayo Clinic trustee 
• Micky Tripathi, Ph.D., chief AI implementation officer at Mayo Clinic 
• Yong Chen, Ph.D., director of the Center for Health AI and Synthesis of Evidence at the Perelman School of Medicine, University of Pennsylvania 
• Yi Qian, vice president of Global Real-World Evidence at Johnson & Johnson  
• Matt Redlon, chair, AI Program, and vice president, Digital Biology, Mayo Clinic Digital Pathology   

Register by May 30 on the event website. 

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