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
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Anticipated)
Enrollment
Contacts and Locations
Study Locations
-
-
-
Hong Kong, Hong Kong
- University of Hong Kong
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
There will be three subsets of study population in this study; patients who were
- RT-PCR confirmed COVID-19 positive
- RT-PCR confirmed COVID-19 negative
- either had a diagnosis of pneumonia before the 1st January 2020.
Description
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
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
RT-PCR Positive Patients
RT-PCR confirmed patients positive for SARS-CoV-2
|
Deep Learning CNN model
|
|
Negative patients
RT-PCR confirmed patients negative for SARS-CoV-2 or patients with CXR performed before the emergence of COVID-19 pandemic
|
Deep Learning CNN model
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Diagnostic Performance of AI model
Time Frame: 9 months
|
Performance (accuracy, sensitivity, specificity, false-positive rate (FPR), false-negative rate (FNR), and Area Under the Curve (AUC)) of the AI model in detection of COVID-19 pneumonia on their baseline CXR using RT-PCR and historical controls as gold standard in a multi-center / multi-national cohort.
|
9 months
|
Collaborators and Investigators
Sponsor
Sponsor
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Anticipated)
Primary Completion
Study Completion (Anticipated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- EN-092020
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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