Siemens Healthineers is collaborating with the Fraunhofer Institute for Medical Image Computing (MEVIS) to develop artificial intelligence (AI) software to support diagnosis and therapy.
The companies recently signed a four-year partnership to develop and market AI-enabled decision support systems, and announced the partnership at last week's German Radiology Congress (Deutscher Röntgenkongress, RöKo 2017).
The companies noted the recent trend toward integrating patient data such as image data, lab values, digital patient records, and surgery reports that previously have been handled separately. This creates the possibility that self-learning computer algorithms could be used to detect hidden patterns in data, giving physicians support for their diagnostic and therapy decisions.
Working together, Siemens and Fraunhofer MEVIS will develop software that helps physicians determine the best therapeutic decisions, providing all the information that would be available to make a diagnostic decision, meaning physicians would no longer have to gather data from multiple sources. Also, guidelines from clinical societies also could be incorporated into the software.
![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)
