Predicting coronary disease risk based on short-term RR interval measurements: a neural network approach

@article{Azuaje1999PredictingCD,
  title={Predicting coronary disease risk based on short-term RR interval measurements: a neural network approach},
  author={Francisco Azuaje and Werner Dubitzky and Philippe Lopes and Norman David Black and Kenneth Adamson and Xin Wu and John A. White},
  journal={Artificial intelligence in medicine},
  year={1999},
  volume={15 3},
  pages={275-97}
}
Coronary heart disease is a multifactorial disease and it remains the most common cause of death in many countries. Heart rate variability has been used for non-invasive measurement of parasympathetic activity and prediction of cardiac death. Patterns of heart rate variability associated with respiratory sinus arrhythmia have recently been considered as possible indicators of coronary heart disease risk in asymptomatic subjects. The aim of this work is to detect individuals at varying risk of… CONTINUE READING
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