A team of international researchers has built an artificial intelligence (AI) tool that can predict how much extra oxygen a Covid-19 patient might need.

Over 20 hospitals worldwide in collaboration with NVIDIAA — a leader in AI technology — tested a new AI-based technique, known as federated learning, using data from across five continents.

The technique uses an algorithm to analyse chest X-rays and electronic health data from hospital patients with Covid symptoms.

Once the algorithm had “learned” from the data, the analysis was brought together to build an AI tool — EXAM (electronic medical record (EMR) chest X-ray AI model) — which could predict the oxygen needs of hospital Covid patients anywhere in the world.

The results, published in the journal Nature Medicine, showed it predicted the oxygen needed within 24 hours of a patient’s arrival in the emergency department, with a sensitivity of 95 percent and a specificity of over 88 percent.

To maintain strict patient confidentiality, the patient data was fully anonymised and an algorithm was sent to each hospital so no data was shared or left its location.

“Usually in AI development, when you create an algorithm on one hospital’s data, it doesn’t work well at any other hospital. By developing the EXAM model using federated learning and objective, multimodal data from different continents, we were able to build a generalizable model that can help frontline physicians worldwide,” said Dr. Ittai Dayan, from Mass General Bingham in the US, where the EXAM algorithm was developed.

The outcomes of around 10,000 Covid patients from across the world were analysed in the study.

“Federated learning has transformative power to bring AI innovation to the clinical workflow,” said lead researcher Professor Fiona Gilbert, at the University of Cambridge.

“Federated Learning allows researchers to collaborate and set a new standard for what we can do globally, using the power of AI. This will advance AI not just for healthcare but across all industries looking to build robust models without sacrificing privacy,” added Dr. Mona G Flores, Global Head for Medical AI at NVIDIA.