Using deep learning algorithms to read and triage chest X-rays in less than a minute, qXR* detects abnormal findings. Its patented algorithms can detect a total of 29 findings in a chest X-ray, including detection of multiple findings in the lungs, pleura, heart, bones and diaphragm. qXR can be used to separate normal from abnormal X-rays or as a radiology audit tool, as well as providing pre-read assistance. It reduces the chances of late diagnoses, under diagnoses and even potential misdiagnoses to deliver better patient care.
Gives healthcare workers access to critical data that can save lives on the frontlines
Turnaround time for results is under a minute
Embeds seamlessly within the workflow where a PACS is in use
Significantly reduces time to TB diagnosis from days, to a couple of hours
Detects ground-glass opacities and consolidation that indicate COVID-19 infections, and quantifies affected lung volume.
Delivers a point-of-care screening tool followed by a bacteriological/NAAT confirmation.
Provides sensitivity and specificity equivalent to expert radiologists, and can assist by clustering worklists into distinct buckets of Normal, Abnormal and To-be Reviewed.
- Tried and tested
Leverages convolutional neural networks trained on over 3.5 million scans, and clinically validated in multiple geographies.
*CE Marked, not available for sale in the United States
“Qure’s AI allows decisions to be made more quickly and more safely, it’s another layer of information to use when deciding on the appropriate treatment. It gives us an objective way at assessing how much the lung has been damaged and shows us other different abnormalities, and where they are.”
Dr Rizwan Malik, NHS Bolton
“Qure.ai's chest X-ray solution helps in early identification of probable TB cases and helps doctors in fast-tracking of TB patients for confirmatory diagnosis. AI will act as a force multiplier for early and fast detection.”
Dr Shibu Vijayan, Director TB/HIV, PATH India