By ScienceDaily
Publication Date: 2026-02-21 00:00:00
In an early real-world test of artificial intelligence in health research, scientists at UC San Francisco and Wayne State University discovered that generative AI can process massive medical data sets far faster than traditional informatics teams – and in some cases can produce even better results. Human experts had spent months carefully analyzing the same information.
In order to be able to directly compare performance, the researchers assigned identical tasks to different groups. Some teams relied solely on human expertise, while others used scientists working with AI tools. The challenge was to predict preterm birth using data from more than 1,000 pregnant women.
Even a young research pair consisting of a UCSF master’s student, Reuben Sarwal, and a high school student, Victor Tarca, successfully developed AI-powered predictive models. The system generated working computer code in minutes – something that would normally take experienced programmers several hours or even days.
The…
