Aortic Stenosis Clinical Trial
Official title:
Phonokardiographie Bei Erwachsenen
Background: Computer aided auscultation in the differentiation of pathologic (AHA class I)
from no- or innocent murmurs (AHA class III) via artificial intelligence algorithms could be
a useful tool to assist healthcare providers in identifying pathological heart murmurs and
may avoid unnecessary referrals to medical specialists.
Objective: Assess the quality of the artificial intelligence (AI) algorithm that autonomously
detects and classifies heart murmurs as either pathologic (AHA class I) or as no- or innocent
(AHA class III).
Hypothesis: The algorithm used in this study is able to analyze and identify pathologic heart
murmurs (AHA class I) in an adult population with valve defects with a similar sensitivity
compared to medical specialist.
Methods: Each patient is auscultated and diagnosed independently by a medical specialist by
means of standard auscultation. Auscultation findings are verified via gold-standard
echocardiogram diagnosis. For each patient, a phonocardiogram (PCG) - a digital recording of
the heart sounds - is acquired. The recordings are later analyzed using the AI algorithm. The
algorithm results are compared to the findings of the medical professionals as well as to the
echocardiogram findings.
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