Data management vendor Segmed and Bayer in Radiology have announced that Bayer will integrate Segmed’s real-world imaging data network product into Bayer’s AI Innovation Platform to accelerate the development of AI-powered healthcare applications
The aim of the collaborative agreement is to help researchers and developers obtain real-world imaging data to build scalable and compliant AI-powered medical imaging software products.
Segmed acquires, deidentifies, standardizes, and provides medical imaging data to researchers, technology developers, and healthcare providers through a web interface.
Bayer’s cloud-based end-to-end software development platform is designed to streamline and accelerate the development, validation, and deployment of imaging-based AI and machine-learning healthcare applications.
![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)
