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Clinical Trial Summary

The management of COVID-19 patients in overwhelmed hospital facing the pandemic is a clinical challenge. The improvement of decision making may allow a better allocation of available resources and a better treatment of patients at higher risk. Chest CT has been widely adopted for COVID-19 pneumonia diagnosis. Several experiences documented the capability of Artificial Intelligence to improve and fasten COVID-19 pneumonia detection, mainly using chest X-ray. Aim of the present study was to develop and validate an Artificial Intelligence approach integrating clinical and imaging data (automatically extracted through the adoption of dedicated neural networks) for the creation of a cloud platform capable of performing automatic patients risk stratification. Such an approach could be used for triage of COVID-19 patients in the emergency department, with the aim to improve healthcare personnel decision-making and allocation of resources during health emergencies.


Clinical Trial Description

n/a


Study Design


Related Conditions & MeSH terms


NCT number NCT04834934
Study type Observational
Source IRCCS San Raffaele
Contact Antonio Esposito, MD
Phone +390226436102
Email esposito.antonio@unisr.it
Status Recruiting
Phase
Start date February 16, 2020
Completion date June 2021

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