06/08/2026
I am excited about the multitude of ways artificial intelligence (AI) can be applied to patient care and am conducting research with Cornelius Thiels, D.O., whose lab focuses on surgical outcomes and applications of AI. Our team was inspired by the clinical need for an effective screening tool for pancreatic cancer, which is projected to become the second leading cause of cancer-related death in the U.S. by 2030.
One way to improve outcomes is to identify patients with cancer at an early stage when treatment may be more effective. However, screening for pancreatic cancer can be expensive, impractical and ineffective. AI is able to take large amounts of data and find meaningful patterns, an exceedingly difficult task for humans. We hypothesized that patient records and lab results over time may reveal patterns, or “signals,” that we can use to identify people who are at higher risk of developing pancreatic cancer. Using Mayo Clinic Platform, our team developed an AI model that integrates de-identified longitudinal data to help predict pancreatic cancer risk. The hope is that this model may be implemented as part of a digital screening approach to help identify people who are at the highest risk and thereby ensure that they receive timely treatment.
I presented our work in a brief “lightning talk” at Mayo Clinic’s 2026 . With the ability of AI to transform and translate large amounts of data, our teams will hopefully be able to get one step closer to finding answers to problems that were previously unsolved.