Machine Learning and End-to-End Deep Learning for the Detection of Chronic Heart Failure From Heart Sounds

@article{Gjoreski2020MachineLA,
  title={Machine Learning and End-to-End Deep Learning for the Detection of Chronic Heart Failure From Heart Sounds},
  author={Martin Gjoreski and Anton Gradi{\vs}ek and Borut Budna and Matja{\vz} Gams and Gregor Poglajen},
  journal={IEEE Access},
  year={2020},
  volume={8},
  pages={20313-20324}
}
Chronic heart failure (CHF) affects over 26 million of people worldwide, and its incidence is increasing by 2% annually. Despite the significant burden that CHF poses and despite the ubiquity of sensors in our lives, methods for automatically detecting CHF are surprisingly scarce, even in the research community. We present a method for CHF detection based on heart sounds. The method combines classic Machine-Learning (ML) and end-to-end Deep Learning (DL). The classic ML learns from expert… 
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