Detection of atrial fibrillation via artificial intelligence-assisted auscultation

The AI-based electronic stethoscope shows promise as a reliable and accessible tool for AF screening, with potential applications in primary healthcare and general population screening.

Authors

Institutions

Publication Details

Journal
BMC Cardiovascular Disorders
Published
2025-11-07
DOI
https://doi.org/10.1186/s12872-025-05236-z
Citations
2
Primary Topic
Phonocardiography and Auscultation Techniques
Type
article
Field-Weighted Citation Impact
3.04
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Detection of atrial fibrillation via artificial intelligence-assisted auscultation

Yongzhe Guo, Huizhong Lin, Yukun Luo, Hui Chen et al.
2 citations
BMC Cardiovascular Disorders
Phonocardiography and Auscultation Techniques
3.04
article

Detection of atrial fibrillation via artificial intelligence-assisted auscultation

Yongzhe Guo, Huizhong Lin, Yukun Luo, Hui Chen, Xianhong Wu
article en
2 citations

Abstract

The AI-based electronic stethoscope shows promise as a reliable and accessible tool for AF screening, with potential applications in primary healthcare and general population screening.

BMC Cardiovascular DisordersVol. 25(1)
Fujian Medical University (CN), Fujian University of Technology (CN)
Openalex Percentile: Top 7%
Phonocardiography and Auscultation Techniques
3.04
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.