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Digipredict digital twin will predict the evolution of Covid-19

Under a cross-disciplinary program spearheaded by EPFL, scientists will develop an AI-based system that can predict whether Covid-19 patients will develop severe cardiovascular complications and, in the longer term, detect the likely onset of inflammatory disease.
Covid-19 comes with a range of symptoms – from a sore throat and the loss of taste to more serious ones like lung failure. But how can doctors predict how serious the disease will be when it first manifests? “The interaction between the viral infection, the host’s response, and the development of cardiovascular inflammation and injury is still poorly understood. It’s hard to know whether a patient’s symptoms will remain mild or rapidly deteriorate and trigger multiple organ failure,” says Adrian Ionescu, a professor at EPFL’s Nanoelectronic Devices Laboratory, within the School of Engineering. If doctors could use a scientific method to better understand and predict the likelihood of a patient’s condi ....

Adrian Ionescu , Wolf Hautz , Alexander Meyer , Stichting Imec , Kamiar Aminian , Jan Kerschgens , David Atienza , Martin Jaggi , University Of Twente , Optimization Laboratory , Nanoelectronic Devices Laboratory , School Of Engineering , University Of Bern , Laboratory Of Movement Analysis , Systems Laboratory , German Heart Center Berlin , Intelligent Systems , Devices Laboratory , Embedded Systems Laboratory , Movement Analysis , Machine Learning , Alexander Meyer Chief Medical Information Officer , Data Science , Executive Director , அலெக்சாண்டர் மேயர் , டேவிட் ஆதிேன்ச ,

Digipredict digital twin will predict evolution of Covid-19

© 2020 EPFL
Under a cross-disciplinary program spearheaded by EPFL, scientists will develop an AI-based system that can predict whether Covid-19 patients will develop severe cardiovascular complications and, in the longer term, detect the likely onset of inflammatory disease.
Covid-19 comes with a range of symptoms – from a sore throat and the loss of taste to more serious ones like lung failure. But how can doctors predict how serious the disease will be when it first manifests? “The interaction between the viral infection, the host’s response, and the development of cardiovascular inflammation and injury is still poorly understood. It’s hard to know whether a patient’s symptoms will remain mild or rapidly deteriorate and trigger multiple organ failure,” says Adrian Ionescu, a professor at EPFL’s Nanoelectronic Devices Laboratory, within the School of Engineering. If doctors could use a scientific method to better understand and predict the likelihood of a ....

Adrian Ionescu , Wolf Hautz , Alexander Meyer , Stichting Imec , Kamiar Aminian , Jan Kerschgens , David Atienza , Martin Jaggi , University Of Twente , Optimization Laboratory , Nanoelectronic Devices Laboratory , School Of Engineering , University Of Bern , Laboratory Of Movement Analysis , Systems Laboratory , German Heart Center Berlin , Intelligent Systems , Devices Laboratory , Embedded Systems Laboratory , Movement Analysis , Machine Learning , Alexander Meyer Chief Medical Information Officer , Data Science , Executive Director , அலெக்சாண்டர் மேயர் , டேவிட் ஆதிேன்ச ,