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AI-based System for Assessing Suspected Viral Pneumonia Related Lung Changes

NCT06501599 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 563

Last updated 2024-07-22

No results posted yet for this study

Summary

The AI-based system designed to process chest computed tomography (CT) aims to 1) detect the presence of pathologic patterns associated with interstitial changes in pneumonia; 2) highlight areas on the images with the probable presence of pathologies; 3) provide the physician with the results of image processing, including quantitative indicators of suspected viral pneumonia related lung changes according to visual pulmonary lesion grading system (CT0-4).

The retrospective study aims to demonstrate the clinical validation of the AI-based system. Clinical validation measures (sensitivity, specificity, accuracy, and area under the ROC curve) will be determined to provide evidence about the clinical efficacy of the AI-based system.

The hypothesis is that the measures of clinical validation of the AI-based system differ by no more than 8% from those declared by the manufacturer.

Conditions

Interventions

DIAGNOSTIC_TEST

Medical software (AI-based system)

Retrospective analysis of chest CT images with medical software (AI-based system)

Sponsors & Collaborators

  • Sciberia Co. Ltd

    collaborator UNKNOWN

  • Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2024-06-03
Primary Completion
2025-06-03
Completion
2025-12-03

Countries

  • Russia

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 NCT06501599 on ClinicalTrials.gov