Researchers at the Whiting School of Engineering and Johns Hopkins Kimmel Cancer Center—founding members of the Cancer AI Alliance (CAIA)—have announced two new projects that showcase how artificial intelligence can transform cancer research and patient care.
As the only research university and comprehensive health system in CAIA, Johns Hopkins brings together world-renowned expertise across medicine, engineering, and public health. The Malone Center for Engineering in Healthcare, Kimmel Cancer Center, Data Science and AI Institute (DSAI), and inHealth Precision Medicine program all play key roles in the initiative.
CAIA, established in 2024, is built on a federated learning platform, which allows each of the participating cancer centers to keep their data secure while developing and sharing AI models.
“AI tools travel to the data, not the other way around,” explains Vasan Yegnasubramanian, a professor of oncology, pathology, and radiation oncology and molecular radiation sciences and the director of inHealth Precision Medicine at Johns Hopkins. “This preserves privacy while enabling broad collaboration.”
In one project—led by Mathias Unberath, the John C. Malone Associate Professor of Computer Science; Jeff Weaver, director of research analytics; Yegnasubramanian; and Alexis Battle, the director of the Malone Center for Engineering in Healthcare, a professor of biomedical engineering, computer science, and genetic medicine, and the director of research for strategy and partnerships for the DSAI—the research team is fine-tuning a large language model using structured electronic health record data.
The model is being trained to follow patient trajectories over time, learning patterns that would allow it to predict later diagnoses, treatments or test results.
“It shows the potential of tailoring large AI models specifically for patients with cancer,” says Battle. “This project, developed under an aggressive timeline, was a deeply collaborative effort that drew in faculty, students, research IT, and the DSAI’s software engineering team.”
This Johns Hopkins-led study is among eight projects launched under CAIA, which also includes the Fred Hutch Cancer Center, Dana-Farber Cancer Institute, and Memorial Sloan Kettering Cancer Center. Over the next year, CAIA leaders hope to expand to dozens of research models and add more cancer centers to the alliance, tackling challenges from predicting treatment response to understanding rare cancers.
“CAIA allows us to innovate across the full spectrum of cancer,” says Yegnasubramanian. “On one end, we can develop foundational models trained on data from more than a million patients. On the other, we can study rare cancers and develop AI models that improve therapy for patients who previously had little guidance.”
CAIA receives financial and technical support from technology partners Amazon Web Services, Deloitte, the Allen Institute for AI, Google, Microsoft, NVIDIA, and Slalom.
“Together, these projects demonstrate how Johns Hopkins and CAIA are laying the foundation for AI-driven advances that will help us make real progress against some of cancer’s most complex problems,” says Battle.
Excerpted from the Johns Hopkins Medicine Newsroom »
Image Caption: CAIA researchers, from left, Vasan Yegnasubramanian (Johns Hopkins Kimmel Cancer Center), Rafael Irrizary (Dana Farber Cancer Institute), Alexis Battle (Johns Hopkins University Whiting School of Engineering), Jeff Leek (Fred Hutch Cancer Center), Sohrab Shah (Memorial Sloan Kettering Cancer Center), and Brian Bot (Fred Hutch Cancer Center). Image Credit: Cancer AI Alliance