How Transformers Make AI Smarter At the heart of this innovation is a special kind of AI architecture called a transformer neural network. Originally designed for understanding human language (like the AI behind ChatGPT), transformers learn to focus on the most important parts of the data they’re analyzing. Tison and his team are using this technology to analyze medical data instead of text. The AI model learns which parts of a patient’s test results are most important and uses that information to make predictions about their health. “Transformers are designed to figure out what really matters in a patient’s data,” Tison. “It’s similar to a doctor knowing which test results to pay close attention to and which ones aren’t as important.”
Applications to Other Health Issues Developing a completely new way to train medical AI is a bold and challenging goal. Instead of following the usual methods used to build AI for medicine, Tison’s team is trying to redesign the process from the ground up. “If we’re successful, this approach could change how AI is used in medicine,” he said, “not just for heart disease, but for many other conditions as well.” UC Noyce has played a critical role in making this research possible, providing funding to support the team’s work and train the next generation of scientists.
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“The UC Noyce award gave us the chance to do something truly innovative,” Tison said. “It also allowed us to involve a Ph.D. student and a postdoctoral researcher, giving them hands-on experience in cutting-edge AI research.”
Securing NIH Funding The early success of this project helped Tison’s team secure a prestigious NIH New Innovator Award, a highly competitive grant that provides $1.5 million in funding over five years. “The support from the UC Noyce helped us lay the foundation for this work,” Tison explained. “That foundation was key to securing additional funding, which will allow us to push this research even further.” “Our long-term vision is to create AI models that better assist doctors by thinking more like them,” Tison said. “By making AI more aware of the context across a broad range of patient data, we can build smarter tools that may ultimately improve patient care.” ◆
KEY TAKEAWAYS
New AI models are being developed to think more like doctors, combining different types of medical data for better diagnoses. This AI system is being tested on heart disease and is already showing promise, continued refinements will advance the technology. The research uses transformer neural network technology (similar to AI in ChatGPT) to help the system focus on the most important parts of patient data.
30 Impact Report 2023 - 24 | UC NI
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