New research has found that using an artificial intelligence (AI)–enabled digital stethoscope more than doubled the detection of moderate to severe valvular heart disease during routine clinical examinations compared with a conventional stethoscope.
Valvular heart disease affects more than half of adults over the age of 65 but is frequently missed during routine examinations in general practice. The condition can impair heart function, limiting physical activity and increasing the risk of arrhythmias, heart failure, hospitalisation and death. Because symptoms are often absent, vague or non-specific, many individuals remain unaware of the disease until it has progressed.
The study, Artificial-Intelligence-Enabled Digital Stethoscope Improves Point-of-Care Screening for Moderate to Severe Valvular Heart Disease, published in the European Heart Journal – Digital Health, suggests the AI-assisted device could help clinicians identify patients who might otherwise remain undiagnosed.
In this study, 357 patients aged 50 years and older with risk factors for heart disease were examined using both a traditional stethoscope and an AI-enabled digital stethoscope. Participants were recruited from three primary care practices within the same geographic region. The median age was 70 years, and 61.9% were women.
The AI device demonstrated markedly greater sensitivity for detecting heart sound patterns associated with valvular heart disease, achieving 92.3% sensitivity compared with 46.2% for the traditional stethoscope.
Valvular heart disease is very common among older adults, yet it often goes undetected until symptoms are advanced. This delay can lead to preventable complications and worsening health that could have been avoided with earlier diagnosis.
These findings show that an AI-enabled stethoscope is far more effective than a traditional stethoscope at identifying patients with moderate to severe valvular disease in real-world clinical settings. This technology could help patients access echocardiography sooner, receive a formal diagnosis earlier and begin treatment more quickly. At a population level, it could also reduce hospital admissions and overall healthcare costs.
The digital stethoscope captures high-fidelity heart sounds and uses machine-learning algorithms trained to recognise acoustic signatures linked to valvular disease. In contrast, traditional auscultation depends solely on a clinician’s hearing and experience and can be influenced by background noise, time pressures and other environmental factors. Patients identified as at risk in primary care are referred for confirmation by echocardiography.
Artificial intelligence provides an additional analytical layer that highlights abnormalities which may be difficult to detect consistently by ear alone. However, the technology supports rather than replaces clinical judgement.
Researchers also observed that patients assessed with the AI-enabled device appeared more engaged during consultations, possibly because they could hear and visualise what the clinician was evaluating. This may improve trust and encourage adherence to follow-up care.
The authors noted a small reduction in specificity with the AI device, which could increase false positives, but argued that this risk is outweighed by the benefits of earlier detection. Further studies are planned to evaluate performance across broader clinical settings and more diverse populations.
This study adds to growing evidence that artificial intelligence can strengthen traditional clinical tools in a practical and responsible way, empowering health professionals rather than replacing them, and giving them greater confidence in their assessments.
Source: ESC
Image Credit: iStock
