1. Accuracy of an automated system for tuberculosis detection on chest radiographs in high-risk screening.
- Author
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Melendez J, Hogeweg L, Sánchez CI, Philipsen RHHM, Aldridge RW, Hayward AC, Abubakar I, van Ginneken B, and Story A
- Subjects
- Automation, Databases, Factual, Humans, Netherlands, ROC Curve, Retrospective Studies, Sensitivity and Specificity, Software, Mass Screening methods, Radiography, Thoracic standards, Tuberculosis, Pulmonary diagnostic imaging
- Abstract
Setting: Tuberculosis (TB) screening programmes can be optimised by reducing the number of chest radiographs (CXRs) requiring interpretation by human experts., Objective: To evaluate the performance of computerised detection software in triaging CXRs in a high-throughput digital mobile TB screening programme., Design: A retrospective evaluation of the software was performed on a database of 38 961 postero-anterior CXRs from unique individuals seen between 2005 and 2010, 87 of whom were diagnosed with TB. The software generated a TB likelihood score for each CXR. This score was compared with a reference standard for notified active pulmonary TB using receiver operating characteristic (ROC) curve and localisation ROC (LROC) curve analyses., Results: On ROC curve analysis, software specificity was 55.71% (95%CI 55.21-56.20) and negative predictive value was 99.98% (95%CI 99.95-99.99), at a sensitivity of 95%. The area under the ROC curve was 0.90 (95%CI 0.86-0.93). Results of the LROC curve analysis were similar., Conclusion: The software could identify more than half of the normal images in a TB screening setting while maintaining high sensitivity, and may therefore be used for triage.
- Published
- 2018
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