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AI4COVID-19: AI Enabled Preliminary Diagnosis for COVID-19 from Cough Samples via an App

arXiv 2004.01275 ↗First posted 2 Apr 2020eess.AS cs.LG cs.SDcited by 48

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Abstract (arXiv)

Background: The inability to test at scale has become humanity's Achille's heel in the ongoing war against the COVID-19 pandemic. A scalable screening tool would be a game changer. Building on the prior work on cough-based diagnosis of respiratory diseases, we propose, develop and test an Artificial Intelligence (AI)-powered screening solution for COVID-19 infection that is deployable via a smartphone app. The app, named AI4COVID-19 records and sends three 3-second cough sounds to an AI engine running in the cloud, and returns a result within two minutes. Methods: Cough is a symptom of over thirty non-COVID-19 related medical conditions. This makes the diagnosis of a COVID-19 infection by cough alone an extremely challenging multidisciplinary problem. We address this problem by investigating the distinctness of pathomorphological alterations in the respiratory system induced by COVID-19 infection when compared to other respiratory infections. To overcome the COVID-19 cough training data shortage we exploit transfer learning. To reduce the misdiagnosis risk stemming from the complex dimensionality of the problem, we leverage a multi-pronged mediator centered risk-averse AI architecture. Results: Results show AI4COVID-19 can distinguish among COVID-19 coughs and several types of non-COVID-19 coughs. The accuracy is promising enough to encourage a large-scale collection of labeled cough data to gauge the generalization capability of AI4COVID-19. AI4COVID-19 is not a clinical grade testing tool. Instead, it offers a screening tool deployable anytime, anywhere, by anyone. It can also be a clinical decision assistance tool used to channel clinical-testing and treatment to those who need it the most, thereby saving more lives.

Key facts. Cited by 48 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Apr 2020.

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Citing papers per year: 2021: 21; 2022: 10; 2023: 3; 2024: 4; 2025: 8; 2026: 2.

48 papers.

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  1. 2021CovidGAN: Data Augmentation Using Auxiliary Classifier GAN for Improved Covid-19 Detectioncited by 64
  2. 2022Vocalsound: A Dataset for Improving Human Vocal Sounds Recognitioncited by 62
  3. 2021Sounds of COVID-19: exploring realistic performance of audio-based digital testingcited by 20
  4. 2021Exploring Self-Supervised Representation Ensembles for COVID-19 Cough Classificationcited by 16
  5. 2021A Generic Deep Learning Based Cough Analysis System from Clinically Validated Samples for Point-of-Need Covid-19 Test and Severity Levelscited by 12
  6. 2022Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkerscited by 12
  7. 2021Biometrics in the Era of COVID-19: Challenges and Opportunitiescited by 11
  8. 2021Statistical Perspectives on Reliability of Artificial Intelligence Systemscited by 10
  9. 2021COVID-19 Detection in Cough, Breath and Speech using Deep Transfer Learning and Bottleneck Featurescited by 9
  10. 2021Virufy: A Multi-Branch Deep Learning Network for Automated Detection of COVID-19cited by 7
  11. 2021COVID-19 Modeling: A Reviewcited by 7
  12. 2021Project Achoo: A Practical Model and Application for COVID-19 Detection from Recordings of Breath, Voice, and Coughcited by 7
36 more
  1. 2021Uncertainty-Aware COVID-19 Detection from Imbalanced Sound Datacited by 6
  2. 2021Benchmarking Uncertainty Quantification on Biosignal Classification Tasks under Dataset Shiftcited by 6
  3. 2021Evaluating the COVID-19 Identification ResNet (CIdeR) on the INTERSPEECH COVID-19 from Audio Challengescited by 5
  4. 2022Exploring Longitudinal Cough, Breath, and Voice Data for COVID-19 Progression Prediction via Sequential Deep Learning: Model Development and Validationcited by 5
  5. 2023Towards using Cough for Respiratory Disease Diagnosis by leveraging Artificial Intelligence: A Surveycited by 5
  6. 2023Transfer Learning to Detect COVID-19 Coughs with Incremental Addition of Patient Coughs to Healthy People's Cough Detection Modelscited by 5
  7. 2022COVID-19 Detection from Respiratory Sounds with Hierarchical Spectrogram Transformerscited by 4
  8. 2025Robust COVID-19 Detection from Cough Sounds using Deep Neural Decision Tree and Forest: A Comprehensive Cross-Datasets Evaluationcited by 4
  9. 2021End-2-End COVID-19 Detection from Breath & Cough Audiocited by 2
  10. 2021Deep Neural Network Based Respiratory Pathology Classification Using Cough Soundscited by 2
  11. 2022A Summary of the ComParE COVID-19 Challengescited by 2
  12. 2022Automatic Tuberculosis and COVID-19 cough classification using deep learningcited by 2
  13. 2022L3-Net Deep Audio Embeddings to Improve COVID-19 Detection from Smartphone Datacited by 2
  14. 2025Cough Classification using Few-Shot Learningcited by 2
  15. 2021Cough Detection Using Selected Informative Features from Audio Signalscited by 1
  16. 2021Automatic COVID-19 disease diagnosis using 1D convolutional neural network and augmentation with human respiratory sound based on parameters: cough, breath, and voicecited by 1
  17. 2022COVYT: Introducing the Coronavirus YouTube and TikTok speech dataset featuring the same speakers with and without infectioncited by 1
  18. 2025Detection of Disease on Nasal Breath Sound by New Lightweight Architecture: Using COVID-19 as An Examplecited by 1
  19. 2025XAI-Driven Spectral Analysis of Cough Sounds for Respiratory Disease Characterizationcited by 1
  20. 2021Impact of data-splits on generalization: Identifying COVID-19 from cough and contextcited by 0
  21. 2021Multimodal Detection of COVID-19 Symptoms using Deep Learning & Probability-based Weighting of Modescited by 0
  22. 2021An Ensemble-based Multi-Criteria Decision Making Method for COVID-19 Cough Classificationcited by 0
  23. 2021Responding to Challenge Call of Machine Learning Model Development in Diagnosing Respiratory Disease Soundscited by 0
  24. 2022On the pragmatism of using binary classifiers over data intensive neural network classifiers for detection of COVID-19 from voicecited by 0
  25. 2022Coswara: A website application enabling COVID-19 screening by analysing respiratory sound samples and health symptomscited by 0
  26. 2023Early Detection of Tuberculosis with Machine Learning Cough Audio Analysis: Towards More Accessible Global Triaging Usagecited by 0
  27. 2024An AI-enabled Bias-Free Respiratory Disease Diagnosis Model using Cough Audio: A Case Study for COVID-19cited by 0
  28. 2024Rene: A Pre-trained Multi-modal Architecture for Auscultation of Respiratory Diseasescited by 0
  29. 2024Sustaining model performance for covid-19 detection from dynamic audio data: Development and evaluation of a comprehensive drift-adaptive frameworkcited by 0
  30. 2024From Lab to Pocket: A Novel Continual Learning-based Mobile Application for Screening COVID-19cited by 0
  31. 2025Principles and Components of Federated Learning Architecturescited by 0
  32. 2025Automatic Cough Analysis for Non-Small Cell Lung Cancer Detectioncited by 0
  33. 2025CoughViT: A Self-Supervised Vision Transformer for Cough Audio Representation Learningcited by 0
  34. 2025A XAI-based Framework for Frequency Subband Characterization of Cough Spectrograms in Chronic Respiratory Diseasecited by 0
  35. 2026Unlocking In-Context Learning in Audio-Language Models from Decentralized Medical Audiocited by 0
  36. 2026From Sound to Symptom: Real-Time Respiratory Signal Understanding for Conversational Healthcare Agentscited by 0