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Development and Validation of Deep Learning–Based Infectivity Prediction in Pulmonary Tuberculosis Through Chest Radiography: Retrospective Study

Development and Validation of Deep Learning–Based Infectivity Prediction in Pulmonary Tuberculosis Through Chest Radiography: Retrospective Study

The sensitivity of traditionally used smear tests is highly variable, ranging from 50% to 60% [4]. Thus, these tests may not detect PTB, particularly when there are low bacterial loads, and are unreliable for early diagnosis. This problem can increase the risk of missing PTB in its early stages and result in patients with asymptomatic or mild symptoms not receiving appropriate diagnosis and treatment [5].

Wou young Chung, Jinsik Yoon, Dukyong Yoon, Songsoo Kim, Yujeong Kim, Ji Eun Park, Young Ae Kang

J Med Internet Res 2024;26:e58413