CompletedNot Applicable

Convolutional Neural Network Model to Detect Coronavirus Disease 2019 (COVID-19) Pneumonia in Chest Radiographs

Colombia3,599 participantsStarted 2021-08-26

Plain-language summary

This study aims to design a Convolutional Neural Network (CNN) and apply an attention model to help differentiate pneumonia due to Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), pneumonia due to other viruses/bacteria, and normal chest x-ray (CXR) in clinical practice. A bank of digital chest images from a high-complexity health facility in Cali, Colombia, was used.

Who can participate

Age range18 Years

SexALL

See this in plain English?

AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.

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

What they're measuring

COVID-19 (coronavirus disease 2019) pneumonia chest radiograph identified

Timeframe: month 8

Trial details

NCT IDNCT05722665

SponsorFundacion Clinica Valle del Lili

Sponsor typeOTHER

Study typeOBSERVATIONAL

Primary completion2022-11-30

View on ClinicalTrials.gov More COVID-19 (Coronavirus Disease 2019) trials