Stefan Hegselmann

May 19, 2024 | nature.com | Benjamin Wild |Maik Pietzner |Stefan Hegselmann |Harry Hemingway |Claudia Langenberg |Ulf Landmesser | +1 more

AbstractThe COVID-19 pandemic exposed a global deficiency of systematic, data-driven guidance to identify high-risk individuals. Here, we illustrate the utility of routinely recorded medical history to predict the risk for 1883 diseases across clinical specialties and support the rapid response to emerging health threats such as COVID-19. We developed a neural network to learn from health records of 502,460 UK Biobank.