GLEAMER Raises € 7.5 Million to Market A.I. Platform Offering Radiologists Semi-automated Diagnosis of Medical Images

Ariane Esmerian


GLEAMER, a French med-tech company that develops an A.I. software platform to help radiologists diagnose their patients, announces it has secured € 7.5 million in a Series A round led by XAnge, alongside new investors MACSFMajycc eSanté Invest, and Crista Galli Ventures, as well as previous investors Elaia and the state-run fund Ambition Amorçage Angels (F3A), which is managed by Bpifrance as part of its Investments for the Future Program (PIA). In addition, 37 radiologists participated in this round, which is expected to boost the market launches of BoneView®, the first A.I. application in the company’s software line, in Europe, the Middle East, Asia, and Latin America. The funds raised will also be used to obtain the Food and Drug Administration (F.D.A.) clearance to market BoneView® in the U.S. and to keep developing GLEAMER’s A.I. product line in other areas of radiology.

Today, the world’s emergency radiology market is worth 12 billion euros (Source: GLEAMER). The need for medical imaging has vastly increased, with more than 400 million medical images produced every year for traumatic injuries worldwide. It is the most common medical examination in emergency rooms. GLEAMER supports radiologists by providing them with an A.I. software that produces a semi-automated diagnosis of traumatic injuries from medical images.

GLEAMER’s first software, BoneView®, detects traumatic injuries in radiographic images and submits them to radiologists for final validation, thus providing health professionals with a safe, reliable, time-saving, and user-friendly tool. GLEAMER conducted an ambitious clinical study with BoneView®, involving 6 radiologists and 6 E.R. doctors who interpreted 600 traumatic injuries based on medical images, half of them with BoneView® and the other half without it. The cross-examination of A.I. and health professionals lowered the rate of undetected traumatic injuries by 30%, while significantly reducing the time required to analyze X-rays.



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