AI software can detect tuberculosis from chest x-rays at an accuracy level comparable to, or better than, that of the radiologists tested, new research indicates.
With the AI method, a simple image of a chest x-ray developed on film and captured with a mobile phone could be sent to a central location for analysis, which could be particularly helpful in low-resource areas, where TB is often concentrated.
Frauke Rudolf, PhD, Department of Infectious Diseases, Aarhus University Hospital, Aarhus, Denmark, and colleagues compared the performance of the AI software in spotting TB with chest x-rays with that of two Ethiopian radiologists with different levels of experience. Rudolf said both had at least 10 years of experience.
Researchers analyzed chest x-rays from 498 patients. Fifty-seven of patients had been diagnosed with TB, 41 clinically and 16 through polymerase chain reaction tests. Neither of the radiologists nor the AI platform was given clinical or laboratory information to accompany the x-rays.The less experienced radiologist's assessments had a sensitivity of 62.5% and a specificity of 91.7%. The more experienced radiologist's assessments had sensitivity of 75% and specificity of 82%.
Patients in this study were adults with TB-indicative symptoms presenting at three public centers in Bissau, Guinea-Bissau in west Africa, and three public health centers in Gondar, Ethiopia.
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