Related Experiment Videos

[MS-DTNet: an efficient model combining multi-scale convolution and dual-tower attention for detecting abnormal heart

Yaoqi Wen1, Xueqi Lu1, Qiucen Wu1

  • 1School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China.

Nan Fang Yi Ke Da Xue Xue Bao = Journal of Southern Medical University
|June 25, 2026
PubMed
Summary

A new model, MS-DTNet, efficiently detects abnormal heart sounds using advanced AI. This automated phonocardiogram (PCG) analysis tool aids clinical decisions and multi-source heart sound analysis.

Keywords:
attention mechanismdepthwise separable convolutiondual-tower architecturelightweight neural networkmulti-scale convolutionphonocardiogram classification

Related Concept Videos

Heart Sounds01:15

Heart Sounds

Heart sounds are generated by the turbulence in blood flow due to the closing of heart valves. These sounds are best perceived slightly away from the valves, where the blood flow disseminates the sound.
Auscultation is the process of listening to these internal body sounds using a stethoscope. The heart produces four types of sounds, but only two—S1 and S2—can usually be heard with a stethoscope.
S1, also known as the "lub" sound, is caused by the closure of atrioventricular (A-V) valves at the...