Convolutional Neural Network Model to Detect COVID-19 Infect... | Clinical Trial | StuddyBuddy@endsection Convolutional Neural Network Model to Detect COVID-19 Infection
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Completed NCT05722665

Convolutional Neural Network Model to Detect COVID-19 Infection

Conditions: COVID-19, COVID-19 Pneumonia

Sex: All
Ages: 18 Years – N/A
Healthy volunteers: 1
Enrollment: 3599
Sponsor: Fundacion Clinica Valle del Lili

Location: Colombia

Summary

The purpose of this study is to design a Convolutional Neural Network (CNN) and apply an attention model to help differentiate pneumonia due to SARS-CoV-2, pneumonia due to other causes and normal chest radiographs in clinical practice using a bank of digital chest images from a high complexity health facility in Cali, Colombia.

Eligibility Criteria

Inclusion Criteria:Chest radiographs from patients without COVID-19 or other pneumonia took before the pandemic start date (January 2020)Chest radiographs from patients with COVID-19 confirmed by positive Reverse Transcriptase polymerase chain reaction (RT-PCR) and/or presence of antibodies to COVID-19 and/or positive COVID-19 viral antigen.Chest radiographs from patients without COVID-19 confirmed by a negative Reverse Transcriptase polymerase chain reaction (RT-PCR) and other pneumonia diagnoses taken before the pandemic start date (January 2020)Exclusion Criteria:N/A

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View on ClinicalTrials.gov

Source: ClinicalTrials.gov (NCT05722665). StuddyBuddy aggregates publicly available trial information.