Kathy Dai, MD, Selected for NewYork-Presbyterian Silverman Fellowship
Second-year radiology resident Kathy Dai, MD, was selected for the 2026-27 Silverman Fellowship in Healthcare Innovation by NewYork-Presbyterian’s Innovation Center. Silverman Fellows receive grant support and mentorship for one year to complete projects designed to transform healthcare delivery.
Dai, who joined Columbia Radiology in July 2025 as a diagnostic radiology resident, will focus on the evaluation of artificial intelligence (AI) tools in radiology. More than 75 percent of FDA-approved AI and machine learning-enabled medical tools involve imaging, and thorough evaluation in clinical settings is important to their success.
“Decisions about which technologies are adopted by radiologists carry broad implications for nearly every specialty,” Dai explains. “Even small changes in how imaging findings are interpreted, communicated, or acted upon can have enormous effects on patient care.”
“Radiologists and clinicians directly involved in patient care are best positioned to distinguish hype from real-world benefit. Healthcare innovations should not only improve outcomes, but also improve the experience of healthcare for both patients and providers.”
As a Silverman Fellow, Dai is developing a rigorous understanding of how AI technologies are evaluated, deployed, scaled, and monitored within a complex health system, with a particular focus on tools that increase the utilization of existing radiology data. An initial project involves the management of incidental findings on radiology exams. Together with collaborators from radiology, pulmonology, and the NewYork-Presbyterian Data Shared Services team, she is helping to develop a process for following up on lung nodules that are discovered incidentally on CT scans.
“With increased patient interest in exams such as whole-body MRI, there is potential for a substantial increase in incidental findings. Efficient management of incidental findings is crucial to realizing the benefits of early detection without driving unnecessary interventions and healthcare costs,” says Dai.
Dai received her medical degree from Duke University and has published on the expansion of whole-body MRI and global trends in cardiac imaging. At Columbia, Dai is a co-founder of the Radiology AI Network, an initiative within the Department of Radiology designed to help close the gap between interest in AI and the limited infrastructure within most departments to educate trainees, evaluate emerging tools, and thoughtfully integrate them into clinical practice.