GE HealthCare and Mass General Brigham have launched a research collaboration to build a generative AI tool that pulls together patient data scattered across clinical notes, imaging systems, and treatment plans. The goal is to cut the manual work radiation oncology teams face when preparing cancer patients for treatment - a process that can require up to 17 separate steps just to import the necessary information.
The data fragmentation problem in radiation oncology
Nearly 60% of people with cancer receive radiation therapy. Treatment planning demands data from multiple disconnected health systems, forcing clinicians to manually piece together records, images, and notes. GE HealthCare said this fragmentation slows the path from diagnosis to the start of treatment. The company's existing Intelligent Radiation Therapy (iRT) platform already reduced patient wait times from up to 30 days to eight days by orchestrating those workflows. The new AI research aims to go further.
The planned tool would capture both structured clinical data and unstructured medical information, then surface and summarize relevant patient details for care teams. It will integrate directly into GE's iRT workflow management software once developed.
Building on prior research
The collaboration extends a long-standing relationship between GE HealthCare and Massachusetts General Hospital, a founding member of Mass General Brigham. John Wolfgang, a principal investigator and clinical physicist in the Department of Radiation Oncology at MGB, said, "Our original work demonstrated how technology can remove barriers in care delivery and help clinicians focus more of their time on patients while accelerating time to treatment."
Sam Kandala, GE HealthCare's general manager of therapy guidance, added, "This new collaboration gives us an opportunity to build on that foundation and explore how AI could help clinicians, not only work more efficiently, but also make better use of the information available to them as they personalize treatment for each patient."
A broader oncology AI push
GE HealthCare has been expanding its oncology research footprint. In December, the company began a separate initiative with Mayo Clinic called GEMINI-RT, which focuses on AI-enabled tools that combine radiation with targeted drugs and precision heating. That research also explores how integrated biomarkers and sensors could improve remote patient monitoring by predicting side effects and triggering faster home-based interventions.
Dr. Bryan Traughber, Mayo Clinic's vice chair of innovation for radiation oncology, said at the time, "The combination of research and technological acumen could allow us to model individual patient journeys with precision, enabling radiation therapy treatments that are truly tailored to each patient."
Why this matters for healthcare and research professionals
Radiation oncology teams spend substantial time on data orchestration that does not require clinical judgment - importing records, reconciling formats, hunting for missing images. A generative AI tool that automates these steps could shift clinician hours back toward direct patient care and treatment personalization. For health systems evaluating AI investments, the iRT results offer a concrete benchmark: reducing treatment wait times from 30 days to eight days through workflow integration alone. The addition of generative AI to that foundation signals where radiation oncology software is heading, and what competitors will need to match.
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