Artificial Intelligence - SARS-CoV-2 Risk Evaluation
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Covid19
- Sponsor
- IRCCS San Raffaele
- Enrollment
- 2000
- Locations
- 1
- Primary Endpoint
- Training, testing and validation of an AI platform for predicting Italian first wave Covid-19 patients prognosis.
- Status
- Completed
- Last Updated
- last year
Overview
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.
Investigators
Antonio Esposito
Associate Professor
IRCCS San Raffaele
Eligibility Criteria
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
Outcomes
Primary Outcomes
Training, testing and validation of an AI platform for predicting Italian first wave Covid-19 patients prognosis.
Time Frame: 9 months
Secondary Outcomes
- Validation of the developed AI platform on italian second wave of Covid-19 patients(3 months)