qXR Becomes First AI-Based Chest X-ray Interpretation Tool to Receive CE Certification

Trained on more than one million chest X-rays, qXR detects 15 of the most common chest X-ray abnormalities with an accuracy of more than 90 percent. Taking only milliseconds to run, the product uses a heat map or bounding box to point out abnormalities to the clinician, facilitating rapid confirmation. In settings without trained healthcare professionals, qXR is already being used to screen for tuberculosis, proving a valuable supplement to the existing healthcare systems. There are fewer than five companies globally that have received a CE certification for AI-based radiology products.

“The chest x-ray is the most commonly performed radiology investigation, but one of the toughest to interpret,” said Dr. Shalini Govil, Quality Controller for the Columbia Asia Radiology Group. “Qure.ai’s solution could serve as a radiology assistant, providing a draft report that can be validated by a physician or radiologist. They’ve also come up with technology to visualize what the algorithm sees – a way to ‘see through the computer’s eyes.’ I think this will be a game-changer on the road to building confidence in AI.”

This technology is also being used globally as a screening tool for Tuberculosis. Forty percent of the 10.4 million annual Tuberculosis cases do not get proper care because they’re not properly diagnosed. qXR can substantially speed up the Tuberculosis diagnosis protocol by screening chest X-rays in milliseconds. More details about qXR and its use cases are available at https://www.qure.ai/product/qxr.

“We’re excited to announce this certification, which clears our path to market in many geographies,” said Prashant Warier, Co-Founder and CEO of Qure.ai. “qXR can help doctors quickly and accurately detect and highlight abnormalities, reducing the chances of a missed diagnosis.”

We have also released a web-based interface that allows radiologists to test the performance of qXR. This portal – available at scan.qure.ai – gives users a real-time interpretation of a chest x-ray.