U.K. startup Kheiron Medical Technologies has raised 20 million euros in a funding round to raise cash to validate and commercialize Mia, its artificial intelligence (AI) software for breast cancer screening, according to a 23 September article from VentureBeat.com.
Kheiron intends to use the new investment to further scale up the clinical validation of Mia, including conducting a series of large-scale clinical trials and rollouts in Europe, the U.S., and Asia. The company seeks to rigorously assess and demonstrate the clinical effectiveness and safety of its product.
Mia, or mammography intelligent assessment, is designed to assist radiologists in detecting breast cancer on digital mammograms. The automated support tool integrates directly into existing radiology workflows and can identify early tumors that may appear nearly invisible to the naked human eye.
Following receipt of the CE Mark for Mia in 2018, Kheiron has collaborated with several U.K. National Health Service (NHS) trusts to evaluate the software's potential ability to improve breast screening outcomes. The groups plan to deploy Mia in a real clinical setting in early 2020.
The series A funding round was led by European venture capital firm Atomico, with participation from Connect Ventures, Hoxton Ventures, Greycroft, and Exor Seeds.
![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)
