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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

Recent advancements in medical imaging, specifically chest radiography (CXR), have contributed significantly to the early detection and management of PTB. The use of CXR as a primary PTB screening tool has been reaffirmed by its high sensitivity despite its specificity limitations. Various studies have demonstrated that CXR is instrumental for identifying PTB, especially in vulnerable populations that exhibit a notably higher disease prevalence than the general population [11,12].

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

J Med Internet Res 2024;26:e58413

Evaluation of 2 Artificial Intelligence Software for Chest X-Ray Screening and Pulmonary Tuberculosis Diagnosis: Protocol for a Retrospective Case-Control Study

Evaluation of 2 Artificial Intelligence Software for Chest X-Ray Screening and Pulmonary Tuberculosis Diagnosis: Protocol for a Retrospective Case-Control Study

The specificity of CXR for PTB could be more significant than evaluating symptoms alone, depending on how the CXR is read. Triage using CXR will also help to minimize the number of individuals undergoing bacteriological tuberculosis testing without reducing the detection of true tuberculosis cases [4].

Muhammad Faiz Mohd Hisham, Noor Aliza Lodz, Eida Nurhadzira Muhammad, Filza Noor Asari, Mohd Ihsani Mahmood, Zamzurina Abu Bakar

JMIR Res Protoc 2023;12:e36121