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Ibex Medical Analytics

NHS problem

There’s constant growth in the number of diagnostic tests each year, but no growth in the number of pathologists, leading to capacity issues. The majority of labs are run manually, but digital tools can reduce the average time a pathologist spends on the simpler cases and allow them to spend more time on the more complex ones.

While it’s difficult to know the real rate of error in pathology, errors are estimated to occur in 0.5-5% of cases. A missed cancer (“false negative” error) may result in significantly poorer prognosis, whilst false positives cause avoidable stress for the patient.

The solution

Ibex applies AI to cancer to reduce diagnostic error rates and improve efficiency. The company’s AI-based algorithm analyses biopsy images and can detect and grade cancer and other anomalies. It is the first-ever AI-based cancer diagnosis solution in routine clinical use in a pathology lab.  

Impact

  • Ibex increases accuracy at pathology labs by using AI-based decision support to focus pathologists’ attention on the cases with higher probability of being cancerous and using AI-based quality control on 100% of cases (currently, quality control is performed randomly on 0-10% of cases)
  • Ibex helps reduce the average time pathologists spend on cases, reduce costs and shorten processing times 

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