Artificial intelligence-based stethoscope for the diagnosis of aortic stenosis
نویسندگان
چکیده
Abstract Background Although the stethoscope is used for auscultation in diagnosis of valvular heart disease more than 200 years, its diagnostic accuracy limited and highly dependent on clinical expertise acoustic range human ear. Purpose To develop an electronic stethoscope, based artificial intelligence (AI), aortic stenosis (AS). Methods We developed (VoqxTM, Sanolla) with subsonic capabilities 0–2,000 Hz. Using VoqxTM, we recorded sounds from 100 patients referred echocardiography (derivation group), 50 moderate or severe AS (aortic valve area (AVA) ≤1.5 cm2) without disease, using 5 standard points. An AI supervised learning model was applied to data first patients, construct a algorithm that then tested validation group (50 other 25 AS). Results The derivation included (age 78±9 28 males, AVA=0.87±0.19 cm2, mean gradient 44±16 mmHg, 39 AS) 58±16 males). 1–4 position (all except mitral position), correctly identified 47/50 (sensitivity 94%) 49/50 (specificity 98%), total 96% (Table). (AS: n=25, age 76±9 years,12 AVA=0.88±0.21 41±15 18 AS; No AS: = 59±18 17 21/25 84%) 24/25 96%), 90% (Table 1). Conclusion Our initial findings show can accurately diagnose AS. promising new tool automatic disease. Funding Acknowledgement Type funding sources: Private company. Main source(s): Sanolla Company Table 1
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ژورنال
عنوان ژورنال: European Heart Journal
سال: 2021
ISSN: ['2634-3916']
DOI: https://doi.org/10.1093/eurheartj/ehab724.1588