NCT05889364

AI-based System for Lung Tuberculosis Screening: Diagnostic Accuracy Evaluation

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 308 (actual)
• Sponsor: Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department · Academic / Other
• Sex: All
• Age: 18 Years – 80 Years
• Healthy volunteers: —

Summary

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

Detailed 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.

Conditions

• Tuberculosis, Pulmonary

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	AI-based x-ray analysis and triage ("normal/tuberculosis suspected")	All included x-rays will be analysed by the AI-based system. Then results will be compared with opinions of 2 experienced radiologists (they make peer-review of all included images independently of each other).

Timeline

• Start date: 2018-02-01
• Primary completion: 2018-03-15
• Completion: 2023-12-30
• First posted: 2023-06-05
• Last updated: 2023-06-05

Locations

1 site across 1 country: Russia