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Geographic Domain Shift Precipitates Divergent Failure Modes In Deep Learning Based Tuberculosis Screening: A Multi-National External Validation Study
2026-01-19
respiratory medicine
Title + abstract only
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BackgroundDeep learning algorithms for tuberculosis (TB) screening frequently achieve radiologist-level performance during internal evaluation, yet their reliability often degrades when deployed to populations differing from the training domain. Such degradation is clinically consequential for screening tools, where the World Health Organization (WHO) emphasizes high sensitivity to minimize missed infectious cases. MethodsA DenseNet-121 convolutional neural network was trained using transfer le...
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