behold.ai red dot algorithm identifies chest x-rays of coronavirus patients as abnormal
behold.ai claimed that its artificial intelligence-based red dot algorithm has been shown to have quickly identified chest X-rays from COVID-19 patients as ‘abnormal’.
The UK-based healthtech company expects the ‘instant triage’ to enable an expedited diagnosis of novel coronavirus cases and ensure resources are properly allocated.
According to behold.ai, its red dot algorithm was trained on more than 30,000 chest x-rays (CXRs) with detailed annotations from certified radiologists. The training process is said to have trained the algorithm to classify a CXR and also localize its findings. The localization is rendered via heatmaps to help in understanding and interpreting the output from the x-ray.
Dr Tom Naunton Morgan – Chief Medical Officer at behold.ai said: “The majority of deaths from COVID-19 are due to pneumonia in the lungs of vulnerable patients.
“Pneumonia is a potentially life-threatening condition caused by a number of pathogens including, directly or indirectly, COVID-19 infection. Our algorithm can detect abnormal chest X-rays including pneumonia almost instantly. Out of 28 X-rays reviewed from patients with COVID-19, we correctly identified 85% of them as ‘abnormal’ using red dot.
“As we evaluate further positive cases from across the world, including here in the UK, our results will be further validated. This will increase the utility of our ‘instant triage’ and potentially help reduce the burden on healthcare systems as more and more cases of pneumonia present and require rapid diagnosis.”
behold.ai red dot algorithm identifies chest x-rays of coronavirus patients as abnormal. (Credit: behold.ai)
The US Food and Drug Administration (FDA) recently gave clearance to behold.ai’s algorithm. The healthtech company expects to commercially launch the red dot algorithm later this year in the US.
Simon Rasalingham – Chairman and Chief Executive of behold.ai said: “Our technology can make a big difference to patient safety, and the delivery of care and cost-savings to health services. It is available here and now to help manage the increased burden that will fall on health systems like the NHS in the coming weeks.”