InHealth is set to deploy’s artificial intelligence solution to help with the classification of chest x-rays into normal and abnormal exams, enhancing the quality and accuracy of reporting to improve patient outcomes.

The AI solution will be deployed across InHealth’s entire telereporting service arm. The technology can help radiologists to interpret radiological scans in healthcare settings, with a high degree of accuracy.’s qXR is an EU MDR CE Class IIb certified chest x-ray solution. It will be used to identify which cases are clear of clinically relevant findings, supporting radiologists to read x-rays more accurately and quickly.

The solution will be used by InHealth to support clients in tackling a backlog of chest x-rays while also improving efficiency and quality of reads. In addition, it will allow InHealth to prioritise more clinically urgent cases.

Jonny McDaniell, director of operations – reporting at InHealth, said: “We are excited to be partnering with to deploy qXR AI software into our tele-radiology platform to assist physicians in highlighting life-threatening abnormalities and improve reporting time for critical cases.”

The qXR software is capable of detecting multiple lung abnormalities in under one minute from a chest x-ray. It can accurately assess radiological findings that could indicate a number of lung diseases, including lung cancer, pneumonia, COPD, TB and heart failure.

Darren Stephens, senior vice president & commercial head UK and Europe of, added, “Our partnership with InHealth is a validation to our dominance in the UK radiology AI market. By combining our expertise in medical imaging with InHealth’s commitment to delivering high-quality diagnostic services, we can make a significant impact on patient outcomes. Together, we can advance the frontiers of healthcare and improve the lives of people across the UK.”

InHealth announced in February this year that it had created 20 new jobs in the Yorkshire region after a number of contract wins, including the contract to scale up Scotland’s remote monitoring pathways.