PREDICTION OF CARDIAC ARRHYTHMIA USING RECURRENT NEURAL NETWORKS GATED RECURRENT UNITS WITH CAUSAL DIAGRAM

Authors

  • U.M. Prakash Department of CSE. SRM Institute of Science and Technology Chennai-603203, India Author
  • Anagha Chakravarthi UG student, Department of CSE. SRM Institute of Science and TechnologyChennai-603203, India, Author
  • Gargi Singh Shekhawat UG student, Department of CSE. SRM Institute of Science and TechnologyChennai-603203, India Author

DOI:

https://doi.org/10.61841/awxzzb76

Keywords:

Cardiac Arrhythmia, Prediction, Recurrent neural networks (RNN), Long short-term memory, causality and Gated, recurrent units

Abstract

 Cardiac Arrhythmia is a medical condition in which irregularity in the heart beat is observed. The aim of this paper is to detect said arrhythmia using a dataset containing various patient details. A popular technique is used namely Recurrent neural networks (RNN) in which a comparatively newer technique is used i.e. Gated recurrent units. This is again implemented with the observations from causality diagram to localize on the right attributes to work with.

 

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References

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6. Combining Evidence in Hybrid Medical DecisionSupport Models Maurice E. Cohen, Donna L. Hudson

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9. A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection in Network Traffic Data

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; Saiful Akbar ; Suhono Harso Supangka bienFred M. Agarap

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Published

31.10.2020

Issue

Vol. 24 No. 8 (2020): 24 (8) 2020

Section

Articles

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How to Cite

U.M. Prakash, Chakravarthi, A., & Shekhawat, G. S. (2020). PREDICTION OF CARDIAC ARRHYTHMIA USING RECURRENT NEURAL NETWORKS GATED RECURRENT UNITS WITH CAUSAL DIAGRAM. International Journal of Psychosocial Rehabilitation, 24(8), 12888-12889. https://doi.org/10.61841/awxzzb76