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A Study to Validate and Improve an Automated Image Analysis Algorithm to Detect Tuberculosis in Sputum Smear Slides

NCT05899400 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 400

Last updated 2023-06-12

No results posted yet for this study

Summary

A Study to Validate and Improve an Automated Image Analysis Algorithm to Detect Tuberculosis in Sputum Smear Slides

Conditions

  • Tuberculosis, Pulmonary

Interventions

DIAGNOSTIC_TEST

Diascopic iON Image Analysis System

A scanning digital optical train that images sputum slides for automated analysis by a tuberculosis detecting algorithm

Sponsors & Collaborators

  • National Institutes of Health (NIH)

    collaborator NIH

  • National Institute for Biomedical Imaging and Bioengineering (NIBIB)

    collaborator NIH

  • Diascopic, LLC

    lead INDUSTRY

Principal Investigators

  • Moses Joloba, MD, PhD · Makerere University

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2019-09-15
Primary Completion
2022-10-31
Completion
2022-12-31

Countries

  • Uganda

Study Locations

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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 NCT05899400 on ClinicalTrials.gov