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.
Study Type
OBSERVATIONAL
Enrollment
2,000
IRCCS San Raffaele
Milan, Italy
Training, testing and validation of an AI platform for predicting Italian first wave Covid-19 patients prognosis.
Time frame: 9 months
Validation of the developed AI platform on italian second wave of Covid-19 patients
Time frame: 3 months
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.