Artificial-intelligence-enabled digital stethoscope improves point-of-care screening for moderate-to-severe valvular heart disease

Feb 9, 2026European heart journal. Digital health

AI-powered digital stethoscope improves quick screening for moderate to severe heart valve disease

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Abstract

The AI-augmented digital stethoscope demonstrated a sensitivity of 92.3% for detecting clinically significant valvular heart disease.

Compared to standard analogue auscultation, the AI system significantly increased sensitivity for identifying valvular heart disease (VHD).
The AI-augmented method detected 12 cases of previously undiagnosed moderate to severe VHD, while analogue auscultation identified only 6 cases.
Despite higher sensitivity, the AI-enabled stethoscope had lower specificity than standard care, suggesting more false positives.
The study included 357 patients aged 50 and older who were at risk for heart disease.

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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%,= 0.01) but lower specificity (86.9% vs. 95.6%,< 0.001) compared with SOC. Artificial intelligence detected 12 cases of previously undiagnosed mod+ VHD, while routine auscultation identified 6. P P

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.

Key numbers

92.3%

Sensitivity Increase

Sensitivity of AI-augmented detection vs. standard auscultation

86.9%

Specificity Decrease

Specificity of AI-augmented detection vs. standard auscultation

Undiagnosed Cases Detected

Number of previously undiagnosed VHD cases identified by AI

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Abstract

Key numbers

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