Covid19
Conditions
Keywords
Artificial Intelligence, Covid19, Chest CT
Brief 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.
Interventions
None listed
Sponsors
Regione Lombardia
Orobix Srl
Microsoft Corporation
ASST Bergamo Est
Centro Cardiologico Monzino
NVIDIA Corporation
PORINI Srl
IRCCS San Raffaele
Study design
Observational model
COHORT
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to 100 Years
Healthy volunteers
No
Inclusion criteria
* confirmed SARS-CoV-2 infection with RT-PCR * non contrast chest CT scan performed within 72 hours after admission to the emergency department
Exclusion criteria
* age \< 18 ys
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Training, testing and validation of an AI platform for predicting Italian first wave Covid-19 patients prognosis. | 9 months |
Secondary
| Measure | Time frame |
|---|---|
| Validation of the developed AI platform on italian second wave of Covid-19 patients | 3 months |
Countries
Italy
Outcome results
None listed