Royal Philips and Mass General Brigham are entering a new collaboration to develop and deploy advanced data infrastructure and AI in order to integrate and process healthcare data from various sources.
The two aim to create a scalable, unified, near real-time data and insights ecosystem. Powered by Philips software platforms, the collaboration will make way for clinicians to capture, analyze, and react to data as it is available, according to the firm.
For the collaboration, Mass General Brigham is bringing together the expertise of its biomedical engineering team, clinical sub-specialists, digital teams, and internal AI business unit with Philips’ research and business teams. The two companies will offer data insights, improve data integration, and foster the development of new algorithms.
![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&dpr=2&fit=crop&h=167&q=70&w=250)
