<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>27</volume><submitter>Jiang W</submitter><pubmed_abstract>&lt;h4>Background&lt;/h4>In resource-limited areas, severe shortages of radiologists contribute to high rates of missed pulmonary tuberculosis (PTB) cases when relying solely on conventional chest X-ray (CXR). Although artificial intelligence-powered computer-aided detection (CAD) has proven effective in PTB diagnosis, its real-world performance remains underexplored.&lt;h4>Objective&lt;/h4>This study aimed to evaluate the real-world diagnostic yield of CAD technology as a triage tool for detecting PTB in primary health care facilities in high-burden areas.&lt;h4>Methods&lt;/h4>We conducted a retrospective paired-design diagnostic yield study using CXR images collected from 7 county- and 32 township-level health care facilities in Yichang city between 2022 and 2024 year. All images were retrospectively repr</pubmed_abstract><journal>Journal of medical Internet research</journal><pagination>e83041</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12670047</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>AI-Powered Chest X-Ray for Diagnosing Pulmonary Tuberculosis in County and Township Health Care Facilities in Yichang: Retrospective, Real-World Study.</pubmed_title><pmcid>PMC12670047</pmcid><pubmed_authors>Xiong J</pubmed_authors><pubmed_authors>Liu J</pubmed_authors><pubmed_authors>Shao J</pubmed_authors><pubmed_authors>Zhou P</pubmed_authors><pubmed_authors>Zhang H</pubmed_authors><pubmed_authors>Wang H</pubmed_authors><pubmed_authors>Yu J</pubmed_authors><pubmed_authors>Yang X</pubmed_authors><pubmed_authors>Li Z</pubmed_authors><pubmed_authors>Jiang W</pubmed_authors><pubmed_authors>Jiang X</pubmed_authors><pubmed_authors>Wang Y</pubmed_authors><pubmed_authors>Su X</pubmed_authors></additional><is_claimable>false</is_claimable><name>AI-Powered Chest X-Ray for Diagnosing Pulmonary Tuberculosis in County and Township Health Care Facilities in Yichang: Retrospective, Real-World Study.</name><description>&lt;h4>Background&lt;/h4>In resource-limited areas, severe shortages of radiologists contribute to high rates of missed pulmonary tuberculosis (PTB) cases when relying solely on conventional chest X-ray (CXR). Although artificial intelligence-powered computer-aided detection (CAD) has proven effective in PTB diagnosis, its real-world performance remains underexplored.&lt;h4>Objective&lt;/h4>This study aimed to evaluate the real-world diagnostic yield of CAD technology as a triage tool for detecting PTB in primary health care facilities in high-burden areas.&lt;h4>Methods&lt;/h4>We conducted a retrospective paired-design diagnostic yield study using CXR images collected from 7 county- and 32 township-level health care facilities in Yichang city between 2022 and 2024 year. All images were retrospectively repr</description><dates><release>2025-01-01T00:00:00Z</release><publication>2025 Dec</publication><modification>2026-06-06T07:35:23.024Z</modification><creation>2026-06-06T03:05:49.435Z</creation></dates><accession>S-EPMC12670047</accession><cross_references><pubmed>41328508</pubmed><doi>10.2196/83041</doi></cross_references></HashMap>