GE HealthCare (GEHC) plans to collaborate with health systems in Hawaii and North Carolina on AI-driven hospital operations software.
The company will work with The Queen's Health Systems in Honolulu and Duke Health in Durham, both of which will offer expertise to inform the development of GEHC's forthcoming cloud-first AI and predictive analytics Software as a Service (SaaS) package. The package will incorporate GEHC's hospital operations experience in supporting nearly 500 facilities with its Command Center software, it said.
In other GEHC news, the firm has launched five new projects for its AI Innovation Lab. The new initiatives include the following:
- Development of an agentic AI diagnostic imaging assistant that would be integrated into radiology devices.
- A collaboration with Mass General Brigham and University of Wisconsin-Madison to refine GE HealthCare's MRI foundation model.
- Development of an agentic AI algorithm to help care teams detect, evaluate, and report incidental findings on CT and to guide radiologists in clinical decision making.
- Research that will support sustainable AI in tomographic imaging by using energy-efficient neural networks.
- An internal generative AI algorithm that will allow GEHC field service engineers to troubleshoot equipment faster.















![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&fit=crop&h=112&q=70&w=112)



