Sep, 2021 - By SMI
An algorithm is used to assess chest X-rays and electronic health data from hospitalized patients with COVID indications using the federated learning technique.
Artificial intelligence (AI) was employed by Addenbrooke's Hospital in Cambridge, as well as 20 other hospitals around the world and healthcare technology company NVIDIA, to forecast COVID patients' oxygen demands on a global basis. The pandemic prompted the study, which sought to develop an AI tool that could forecast how much extra oxygen a COVID-19 patient would require in the initial days of hospitalization using data from four continents.
To ensure tight patient confidentiality, all patient data was encrypted, and an algorithm was delivered to each hospital to ensure that no data was exchanged or left its original location. The analysis was brought together to construct an AI tool that could forecast the oxygen demands of hospital COVID patients anywhere around the world once the system had "learned" from the data. EXAM was tested at a number of hospitals across five continents, including Addenbrooke's Hospital, to ensure its accuracy. With a sensitivity of 95% and a specificity of over 88%, the results revealed it could estimate the amount of oxygen needed within 24 hours of a patient's presentation in the emergency room.
The EXAM model, which brought together collaborators from North and South America, Europe, and Asia, took only two weeks of AI "learning" to provide high-quality predictions. The study looked at the outcomes of around 10,000 COVID patients from around the world, which include 250 who visited Addenbrooke's Hospital during the first wave of the pandemic in March/April 2020. The Cambridge Biomedical Research Centre (BRC) and National Institute for Health Research (NIHR) funded the study.
The EXAM model is still being worked on. To undertake prospective trials using EXAM, Mass General Brigham and the NIHR Cambridge BRC are collaborating with NVIDIA Inception startup Rhino Health, co-founded by Dr. Dayan.
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