{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Codlin AJ"],"funding":["Wellcome Trust"],"pagination":["52"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11291606"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["2(1)"],"pubmed_abstract":["<h4>Background</h4>In 2022, fewer than half of persons with tuberculosis (TB) had access to molecular diagnostic tests for TB due to their high costs. Studies have found that the use of artificial intelligence (AI) software for chest X-ray (CXR) interpretation and sputum specimen pooling can each reduce the cost of testing. We modeled the combination of both strategies to estimate potential savings in consumables that could be used to expand access to molecular diagnostics.<h4>Methods</h4>We obtained Xpert testing and positivity data segmented into deciles by AI probability scores for TB from the community- and healthcare facility-based active case finding conducted in Bangladesh, Nigeria, Viet Nam, and Zambia. AI scores in the model were based on CAD4TB version 7 (Zambia) and qXR (all oth"],"journal":["BMC global and public health"],"pubmed_title":["Expanding molecular diagnostic coverage for tuberculosis by combining computer-aided chest radiography and sputum specimen pooling: a modeling study from four high-burden countries."],"pmcid":["PMC11291606"],"funding_grant_id":["209075/Z/17/Z"],"pubmed_authors":["Wingfield T","Squire B","Vo LNQ","Ahmed S","Sanjase N","Abdulkarim S","John S","Codlin AJ","Banu S","Iem V","Garg T","Muyoyeta M","Creswell J"],"additional_accession":[]},"is_claimable":false,"name":"Expanding molecular diagnostic coverage for tuberculosis by combining computer-aided chest radiography and sputum specimen pooling: a modeling study from four high-burden countries.","description":"<h4>Background</h4>In 2022, fewer than half of persons with tuberculosis (TB) had access to molecular diagnostic tests for TB due to their high costs. Studies have found that the use of artificial intelligence (AI) software for chest X-ray (CXR) interpretation and sputum specimen pooling can each reduce the cost of testing. We modeled the combination of both strategies to estimate potential savings in consumables that could be used to expand access to molecular diagnostics.<h4>Methods</h4>We obtained Xpert testing and positivity data segmented into deciles by AI probability scores for TB from the community- and healthcare facility-based active case finding conducted in Bangladesh, Nigeria, Viet Nam, and Zambia. AI scores in the model were based on CAD4TB version 7 (Zambia) and qXR (all oth","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024","modification":"2025-04-21T21:52:01.207Z","creation":"2025-04-21T21:52:01.207Z"},"accession":"S-EPMC11291606","cross_references":{"pubmed":["39100507"],"doi":["10.1186/s44263-024-00081-2"]}}