ArticleSensors (Basel, Switzerland)2023
A Low-Cost AI-Empowered Stethoscope and a Lightweight Model for Detecting Cardiac and Respiratory Diseases from Lung and Heart Auscultation Sounds.
Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Audio-based digital biomarkers in diagnosing and managing respiratory diseases: a systematic review and bibliometric analysis.European respiratory review : an official journal of the European Respiratory Society · 2025Pooled it
- Artificial intelligence in clinical physiology: System-wise applications in diagnostics, monitoring, and medical education.Journal of family medicine and primary care · 2026Article
- Electronic Stethoscope Auscultation and Echocardiography in ARDS: Correlation and Prognostic Value for Mortality and ICU Length of Stay: A Prospective Observational Study.Medicina (Kaunas, Lithuania) · 2026Observational
- Unraveling the neuro-immune axis in cough hypersensitivity: from pathogenesis to synergistic management.Frontiers in medicine · 2026Review
- Artificial Intelligence Enabled Lung Sound Auscultation in the Early Diagnosis and Subtyping of Interstitial Lung Disease.Journal of clinical medicine · 2025Review
- Enhancing Digital Twin Fidelity Through Low-Discrepancy Sequence and Hilbert Curve-Driven Point Cloud Down-Sampling.Sensors (Basel, Switzerland) · 2025Article
- Digital auscultation in clear and present threat of novel respiratory infectious disease: a narrative review.Journal of Yeungnam medical science · 2025Article
- Artificial intelligence (AI) or augmented intelligence? How big data and AI are transforming healthcare: Challenges and opportunities.South African medical journal = Suid-Afrikaanse tydskrif vir geneeskunde · 2023Article
- Artificial intelligence in clinical medicine: catalyzing a sustainable global healthcare paradigm.Frontiers in artificial intelligence · 2023Review
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Cardiac and respiratory diseases are the primary causes of health problems. If we can automate anomalous heart and lung sound diagnosis, we can improve the early detection of disease and enable the screening of a wider population than possible with manual screening. We propose a lightweight yet powerful model for simultaneous lung and heart sound diagnosis, which is deployable in an embedded low-cost device and is valuable in remote areas or developing countries where Internet access may not be available. We trained and tested the proposed model with the ICBHI and the Yaseen datasets. The experimental results showed that our 11-class prediction model could achieve 99.94% accuracy, 99.84% precision, 99.89% specificity, 99.66% sensitivity, and 99.72% F1 score. We designed a digital stethoscope (around USD 5) and connected it to a low-cost, single-board-computer Raspberry Pi Zero 2W (around USD 20), on which our pretrained model can be smoothly run. This AI-empowered digital stethoscope is beneficial for anyone in the medical field, as it can automatically provide diagnostic results and produce digital audio records for further analysis.
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Registered trials
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