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

NCT05722665 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 3599

Last updated 2023-02-23

No results posted yet for this study

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.

Conditions

Interventions

OTHER

Categorization of chest xrays images

Use of Convolutional Neural Network Model to categorize chest xrays images in each group.

Sponsors & Collaborators

  • Universidad Autonoma de Occidente

    collaborator OTHER

  • Fundacion Clinica Valle del Lili

    lead OTHER

Principal Investigators

  • Liliana Fernandez, M.D · Fundacion Clinica Valle del Lili

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2021-08-26
Primary Completion
2022-11-30
Completion
2022-11-30

Countries

  • Colombia

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05722665 on ClinicalTrials.gov