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Clinical Trial Summary

Testing of AI solutions to assess diagnostic accuracy for tuberculosis detection.


Clinical Trial Description

Tuberculosis remains a key problem of modern medicine. New approaches for burden overcoming should be proposed. New screening strategies may include artificial intelligence (AI). An AI-based system for chest x-ray analysis and triage ("normal/tuberculosis suspected") have been developed and trained. A special data-set was prepared. There are 238 normal x-rays and 70 x-rays with lung tuberculosis in data-set. The data-set was randomly divided into 2 samples: - sample N1 (n=140) with ratio "normal: tuberculosis" 50:50, - sample N1 (n=150) with ratio "normal: tuberculosis" 95:5. Both samples will be analysed by AI-based system. Results will be quantified using diagnostic accuracy metrics: sensitivity and specificity, positive and negative predictor values, likelihood ratio, and area under the ROC (receiver operating characteristic) curve. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT05889364
Study type Observational
Source Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department
Contact
Status Active, not recruiting
Phase
Start date February 1, 2018
Completion date December 30, 2023

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