Evaluation of a COVID-19 Pneumonia CXR AI Detection Algorithm

Evaluation of a Chest X-Ray AI Neural Network (RadGen SARS-CoV2 Detection System) for the Detection of RT-PCR Confirmed SARS-Cov2 Covid-19 Pneumonia

This study investigates the diagnostic performance of an AI algorithm in the detection of COVID-19 pneumonia on chest radiographs.

This is an international multi-center study. Chest radiographs (CXR) from different participating centers will be collected to develop an AI algorithm to detect COVID-19 pneumonia. This will be tested on external hold out datasets from different centers using SARS-CoV-2 by Real-Time Reverse Transcriptase-Polymerase Chain Reaction (RT-PCR) Assay as ground truth.

Inclusion Criteria:

• All adult patients >18 years of age
• Attended any of the participating institutes between February 1, 2020 until September, 2020
• Underwent both RT-PCR testing and frontal CXR (within 48 hours of PCR testing) for COVID-19 infection
• frontal CXR of patients pre-covid pandemic

Exclusion Criteria:

• Unavailability of patient demographics and clinical data
• Inconclusive RT-PCR results
• CXR considered to be of non-diagnostic quality by the clinical radiology research team at each site
• CXR not in a retrievable or processable format for AI inference