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 could process enormous medical datasets far faster than traditional computer science teams -- and in some cases produce even stronger results. Human experts had spent months carefully analyzing the same information.
To compare performance directly, researchers assigned identical tasks to different groups. Some teams relied entirely 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 junior research pair made up of a UCSF master student, Reuben Sarwal, and a high school student, Victor Tarca, successfully developed prediction models with AI support. The system generated functioning computer code in minutes -- something that would normally take experienced programmers several hours or even days.
The advantage came from AI ability to write analytical code based on short but highly specific prompts. Not every system performed well. Only 4 of the 8 AI chatbots produced usable code. Still, those that succeeded did not require large teams of specialists to guide them.
Because of this speed, the junior researchers were able to complete their experiments, verify their findings, and submit their results to a journal within a few months.
These AI tools could relieve one of the biggest bottlenecks in data science: building our analysis pipelines, said Marina Sirota, PhD, a professor of Pediatrics who is the interim director of the Bakar Computational Health Sciences Institute at UCSF and the principal investigator of the March of Dimes Prematurity Research Center at UCSF. The speed-up couldn come sooner for patients who need help now.
Sirota is co-senior author of the study, published in Cell Reports Medicine on Feb. 17.
Speeding up data analysis could improve diagnostic tools for preterm birth -- the leading cause of newborn death and a major contributor to long term motor and cognitive challenges in children. In the United States, roughly 1,000 babies are born prematurely each day.
