ArticleInformatics in medicine unlocked2020
AI4COVID-19: AI enabled preliminary diagnosis for COVID-19 from cough samples via an app.
Article in Informatics in medicine unlocked, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 191 papers, 7 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Evaluation of the Artificial Intelligence/Machine Learning-Based Diagnostic Software as a Medical Device Using Forced Cough Vocalization Signal Data Signatures in the Diagnosis of COVID-19 Illness
Evaluation of the Artificial Intelligence/Machine Learning-Based Diagnostic Software as a Medical Device Using Forced Cough Vocalization Signal Data Signatures in the Diagnosis of COVID-19 Illness: A Prospective, Two-Arm Non-Inferiority Clinical Validation Trial of AudibleHealth Dx Software as a Medical Device (EUA-US)
Who cites it
191 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- Cough biomarkers for diagnosis and monitoring of respiratory disease: a systematic review.European respiratory review : an official journal of the European Respiratory Society · 2026Pooled it
- Mobile Apps for COVID-19 Detection and Diagnosis for Future Pandemic Control: Multidimensional Systematic Review.JMIR mHealth and uHealth · 2024Pooled it
- Respiratory Diseases Diagnosis Using Audio Analysis and Artificial Intelligence: A Systematic Review.Sensors (Basel, Switzerland) · 2024Pooled it
- Combating COVID-19 Crisis using Artificial Intelligence (AI) Based Approach: Systematic Review.Current topics in medicinal chemistry · 2024Pooled it
- The Role of Digital Technology in Curbing COVID-19.International journal of environmental research and public health · 2022Pooled it
- X-Ray Equipped with Artificial Intelligence: Changing the COVID-19 Diagnostic Paradigm during the Pandemic.BioMed research international · 2021Pooled it
- Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisalBMJ (Clinical research ed.) · 2020Pooled it
- Deep learning diagnostic and risk-stratification pattern detection for COVID-19 in digital lung auscultations: clinical protocol for a case-control and prospective cohort study.BMC pulmonary medicine · 2021Trial
- Cough Audio Recognition for Early Detection of Respiratory Diseases: Algorithm Development and Validation Study.JMIR medical informatics · 2026Article
- Non-contact lung disease classification via orthogonal frequency division multiplexing-based passive 6G integrated sensing and communication.Communications medicine · 2026Article
- International Partnerships in AI-Driven Healthcare: Opportunities and Challenges for Advancing the UN Sustainable Development Goals-A Perspective.Healthcare (Basel, Switzerland) · 2025Article
- Chronic obstructive pulmonary disease screening using time-frequency features of self-recorded respiratory sounds.JAMIA open · 2025Article
- A Comprehensive Drift-Adaptive Framework for Sustaining Model Performance in COVID-19 Detection From Dynamic Cough Audio Data: Model Development and Validation.Journal of medical Internet research · 2025Article
- Automatic detection and prediction of COVID-19 in cough audio signals using coronavirus herd immunity optimizer algorithm.Scientific reports · 2025Article
- The role of artificial intelligence in pandemic responses: from epidemiological modeling to vaccine development.Molecular biomedicine · 2025Review
- Speech-based respiratory diagnostics: A study on COVID-19 detection with machine learning.PloS one · 2025Article
- Generative AI and unstructured audio data for precision public health.npj health systems · 2025Article
- Low-cost and convenient screening of disease using analysis of physical measurements and recordings.PLOS digital health · 2024Review
- Current Diagnostic Techniques for Pneumonia: A Scoping Review.Sensors (Basel, Switzerland) · 2024Article
- COVID-19 transmission and control in land public transport: A literature review.Fundamental research · 2024Review
131 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 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-s cough sounds to an AI engine running in the cloud, and returns a result within 2 min.
methodsCough 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.
resultsResults 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.