GE Healthcare has chosen seven startup companies to make up the second cohort of its Edison Accelerator program in Europe, Middle East and Africa (EMEA).
The six-month program, which is being held in partnership with Wayra UK, will feature seven firms from four countries:
- Alertive: A tech company that builds mobile and desktop applications for critical-care workers
- xWave Technologies: Founded in 2020 by radiologists, this Irish company is developing a cloud-based platform to support radiology referrals
- Idoven: A healthtech company from Spain that's developing an artificial intelligence (AI) platform for electrocardiogram interpretation
- Nurea: A French startup developing software for standardizing medical image interpretation
- Metalynx: A U.K. firm developing a software visualization platform to enable subject matter experts to develop and evaluate computer-vision applications without technical training
- Kosa AI: A Dutch software company creating AI governance software tools
- Clinithink: A U.K. technology company developing an AI platform capable of understanding unstructured medical notes
The startups will be presented to a network of inventors, potential business partners, and customers during the program. Successful applications may also have the opportunity to be distributed through the GE Healthcare Marketplace.
![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.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&fit=crop&h=100&q=70&w=100)
![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.auntminnieeurope.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)
