Tuberculosis, Pulmonary Clinical Trial
Official title:
AI-based System for Lung Tuberculosis Screening: Diagnostic Accuracy Evaluation
Testing of AI solutions to assess diagnostic accuracy for tuberculosis detection.
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. ;
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