Aims: Valvular heart disease (VHD) can affect more than one in two adults over 65 yet remains underdiagnosed due to the limitations of traditional auscultation. Earlier detection is critical for improving outcomes, but many cases go unrecognized. This study evaluates whether an artificial intelligence (AI)-enabled digital stethoscope can augment primary care providers' (PCPs) ability to detect clinically significant VHD compared with analogue auscultation alone.
Methods and results: In this prospective study, 357 patients aged ≥50 years at risk for heart disease underwent both analogue cardiac auscultation by PCPs (standard of care, SOC) and digital cardiac auscultation by study coordinators followed by AI analysis using an electronic stethoscope (AI-augmented). Echocardiography and audible murmur annotation served as the reference standard. Sensitivity and specificity of AI vs. SOC were compared using Fisher's exact test. The AI-augmented system demonstrated significantly higher sensitivity (92.3% vs. 46.2%, P = 0.01) but lower specificity (86.9% vs. 95.6%, P < 0.001) compared with SOC. Artificial intelligence detected 12 cases of previously undiagnosed mod+ VHD, while routine auscultation identified 6.
Conclusion: Artificial intelligence-enabled digital stethoscopes significantly improve point-of-care VHD detection, offering a promising tool for earlier diagnosis and intervention in primary care settings.
Keywords: Artificial intelligence; Digital stethoscope; Early detection; Primary care; Structural murmur; Valvular heart disease.
© The Author(s) 2026. Published by Oxford University Press on behalf of the European Society of Cardiology.