Why ML-based cough models do not generalize: a systematic cross-dataset evaluation for tuberculosis screening

arXiv:2608.25846 · eess.AS, cs.AI, cs.LG, cs.SD, eess.SP · Submitted 2026-08-26 · Read on arXiv

eess.AS, cs.AI, cs.LG, cs.SD, eess.SP

Submitted: 2026-08-26

Updated: 2026-08-26

Code: https://github.com/esl-epfl/tb-cough-generalization

Terminology

• AUC — 53× in this paper · explained in 2 episodes
• Generalization — 44× in this paper · explained in 13 episodes
• Embeddings — 15× in this paper · explained in 2 episodes
• Feature Selection — 11× in this paper · explained in 4 episodes
• External Validation — 10× in this paper · explained in 2 episodes
• Consistency — 9× in this paper · explained in 3 episodes
• Domain Shift — 6× in this paper · explained in 4 episodes
• Adaptation — 4× in this paper · explained in 1 episode
• Robustness — 4× in this paper · explained in 5 episodes
• Benchmark — 3× in this paper · explained in 2 episodes
• Benchmarking — 3× in this paper · explained in 4 episodes
• Foundation Model — 3× in this paper · explained in 3 episodes
• Generalizability — 3× in this paper · explained in 6 episodes
• Clustering — 2× in this paper · explained in 2 episodes
• Domain Adaptation — 2× in this paper · explained in 5 episodes
• Feature Extraction — 2× in this paper · explained in 2 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Hyperparameters — 2× in this paper · explained in 2 episodes
• Information Leakage — 2× in this paper · explained in 2 episodes
• Adversarial Examples — 1× in this paper · explained in 2 episodes
• Adversarial Training — 1× in this paper · explained in 1 episode
• Centre for Infectious Disease Research in Zambia — 1× in this paper
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Uncertainty Quantification — 1× in this paper · explained in 8 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes

Sources

• TB or not TB? Acoustic cough analysis for tuberculosis classification
• HeAR -- Health Acoustic Representations
• CNN Architectures for Large-Scale Audio Classification
• Optimizing Audio Augmentations for Contrastive Learning of Health-Related Acoustic Signals
• Deep Residual Learning for Image Recognition
• Towards Open Respiratory Acoustic Foundation Models: Pretraining and Benchmarking
• Domain Information Control at Inference Time for Acoustic Scene Classification
• mixup: Beyond Empirical Risk Minimization
• Explaining and Harnessing Adversarial Examples
• Deep Domain Confusion: Maximizing for Domain Invariance

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