Zebra’s AI technology can flag time-critical cases such as pneumothorax in chest x-rays and brain bleeds in CT scans.

The technology reduces the time it takes radiologists and ER staff to spot acute conditions by 80%, the company said, improving the quality and timeliness of treatment.

Zebra’s imaging analytics engine connects to any medical picture archive system and analyses relevant scans with its algorithms.

Once an acute condition is detected, a standard message alerts various systems in the hospital, such as the radiology department or emergency room worklists.

Each hospital can customise the way the alert is presented, either with colour coding or priority ranking, and the technology can be deployed on-premises or via the cloud.

Neither method compromises the workflow, originally acquired images, or risks breaching protected health information data laws, Zebra said.

Pneumothorax, the presence of gas within the pleural space between the lung and the chest wall, remains a globally significant health problem with considerable associated morbidity and healthcare costs. Without prompt management, pneumothorax can lead to total lung collapse and other potentially fatal complications.

It can be spontaneous or can be caused by underlying lung disease, trauma, or complications from biopsies or surgical procedures. With an estimated incidence rate of 18-28 cases per 100,000 population, there are between 130,000 – 207,000 cases of pneumothorax in Europe every year. Misdiagnosis or late-diagnosis of pneumothorax impacts around 74,000 Americans per year.

Brain bleed is even more prevalent and accounts for approximately 8-15% of all strokes in western countries, impacting almost 3.6 million Americans each year.

AI is increasingly being used to detect diseases from scans – the UK’s life sciences tsar Sir John Bell said last year that AI-based systems could save billions for the NHS, halving the health service’s £2.2 billion spend on pathology by detecting common diseases from scans.

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