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In utero Measurement of Heart Rate in Mouse by Noninvasive M-mode Echocardiography
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Intelligent Diagnosis of Heart Murmurs in Children with Congenital Heart Disease

Jiaming Wang1, Tao You2,3, Kang Yi2,3

  • 1Research Center of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang, Jiangsu 212013, China.

Journal of Healthcare Engineering
|May 27, 2020
PubMed

Insights

This study developed an AI tool for diagnosing pediatric congenital heart disease (CHD) murmurs using phonocardiogram (PCG) signals. The intelligent system achieved high accuracy, enabling effective online screening for early detection of CHD in children.

Area of Science:

  • Cardiology
  • Biomedical Engineering
  • Artificial Intelligence

Background:

  • Heart auscultation is crucial for early heart disease diagnosis.
  • Intelligent systems for online medicine are emerging.
  • Limited research exists on intelligent diagnosis of pediatric congenital heart disease (CHD) murmurs.

Purpose of the Study:

  • To develop an intelligent diagnostic method for pediatric CHD murmurs.
  • To improve early detection of congenital heart disease in children.

Main Methods:

  • Collected phonocardiogram (PCG) signals from 86 children (24 normal, 62 with CHD murmurs).
  • Implemented a discrete wavelet transform and Hadamard product for heart sound segmentation.
  • Extracted ten CHD murmur-specific features.
  • Utilized a classification system of 86 artificial neural network classifiers.

Main Results:

  • The system achieved 93% accuracy in diagnosing heart murmurs.
  • Sensitivity was 93.5% and specificity was 91.7%.
  • Successfully identified pediatric CHD murmurs.

Conclusions:

  • An intelligent diagnostic method for pediatric CHD murmurs was successfully developed.
  • The system is suitable for online screening of CHD in children.
  • This approach can aid in early detection and management of pediatric heart conditions.

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