RYVER.AI secures €1.3M Pre-Seed to address bias in radiology diagnostics through generative AI
Summary
It develops generative AI to create diverse sets of artificial radiology images that can not be distinguished from the real world.Responding to the challenges of ethical biasTechnical co-founders Kathrin Khadra and Simona Santamaria, who have a research background in ethics in AI, found that medical AI is not performing reliably across all patient demographics or geographic regions.Various studies have shown that AI-enabled diagnostics in radiology is performing significantly worse for certain demographic and ethnic minorities, leading to structural underdiagnosis of those underrepresented patient groups. This is because datasets to train and test medical AI are heavily biased.About 80 percent of FDA-approved medical AI solutions focus on analysing Radiology images (e.g. XRay, CT, MRI), and suffer from a lack of diverse data.In response, companies spend up to 12 months negotiating collaborations with hospitals or pay up to 500 per radiology image for data acquisition and annotation.RYVER.AI develops generative models that enable medical AI developers to generate diverse sets of synthetic test and training data in minutes and at substantially reduced cost.It protects patient privacy as the synthetic data is not linked directly to real-world patients. Other notable investors include BayernKapital and Fund F. Marta Gaia Zanchi, Managing Partner of Nina Capital, shared:"Most medical imaging data is biased: by definition, it poorly represents underserved communities, new equipment, and rare diseases. RYVER.AIs diverse founding team blends not only the expertise and commitment required to tackle such technical challenges but also a strong North Star guiding them toward its ethical application for the pursuit of more affordable, higher quality medical AI. "The funding will help grow the AI engineering team and finance the computational cost required to build advanced generative models.