Survey of Machine Learning Techniques To Predict Heartbeat Arrhythmias

Samuel Armstrong

Survey of Machine Learning Techniques To Predict Heartbeat Arrhythmias

Machine Learning 2022-08-23 v1 Signal Processing

Authors: Samuel Armstrong

Abstract

Many works in biomedical computer science research use machine learning techniques to give accurate results. However, these techniques may not be feasible for real-time analysis of data pulled from live hospital feeds. In this project, different machine learning techniques are compared from various sources to find one that provides not only high accuracy but also low latency and memory overhead to be used in real-world health care systems.

Keywords

machine learning heartbeat arrhythmias real-time analysis low latency memory overhead healthcare systems

Cite

@article{arxiv.2208.10463,
  title  = {Survey of Machine Learning Techniques To Predict Heartbeat Arrhythmias},
  author = {Samuel Armstrong},
  journal= {arXiv preprint arXiv:2208.10463},
  year   = {2022}
}

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