A Study to Validate and Improve an Automated Image Analysis Algorithm to Detect Tuberculosis in Sputum Smear Slides
NCT ID: NCT05899400
Last Updated: 2023-06-12
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
400 participants
OBSERVATIONAL
2019-09-15
2022-12-31
Brief Summary
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Detailed Description
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Conditions
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Study Design
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COHORT
RETROSPECTIVE
Study Groups
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Study Group
400 Male and Female Ugandan Africans
Diascopic iON Image Analysis System
A scanning digital optical train that images sputum slides for automated analysis by a tuberculosis detecting algorithm
Interventions
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Diascopic iON Image Analysis System
A scanning digital optical train that images sputum slides for automated analysis by a tuberculosis detecting algorithm
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
ALL
No
Sponsors
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National Institutes of Health (NIH)
NIH
National Institute for Biomedical Imaging and Bioengineering (NIBIB)
NIH
Diascopic, LLC
INDUSTRY
Responsible Party
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Principal Investigators
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Moses Joloba, MD, PhD
Role: STUDY_DIRECTOR
Makerere University
Locations
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Makerere University
Kampala, , Uganda
Countries
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Other Identifiers
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Diascopic
Identifier Type: -
Identifier Source: org_study_id
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