mlsanityData to 14 Oct 2026

Using machine learning algorithms to determine the post-COVID state of a person by his rhythmogram

arXiv 2212.13878 ↗First posted 16 Dec 2022eess.SP cs.HC cs.LGcited by 0

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Abstract (arXiv)

In this study we applyed machine-learning algorithms to determine the post-COVID state of a person. During the study, a marker of the post-COVID state of a person was found in the electrocardiogram data. We have shown that this marker in the patient's ECG signal can be used to diagnose a post-COVID state.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 9 of its 85 references that are in the map. First posted on arXiv 16 Dec 2022.

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9 of 85 references.

References · 9

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2017Squeeze-and-Excitation Networkscited by 4,789
  3. 2016Gaussian Error Linear Units (GELUs)cited by 3,502
  4. 2019Searching for MobileNetV3cited by 1,994
  5. 2020A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospectscited by 397
  6. 2021A Survey of Modern Deep Learning based Object Detection Modelscited by 98
  7. 2017Cardiologist-Level Arrhythmia Detection with Convolutional Neural Networkscited by 53
  8. 2022Detecting COVID-19 from digitized ECG printouts using 1D convolutional neural networkscited by 2
  9. 2022Failure of neuron network coherence induced by SARS-CoV-2-infected astrocytescited by 1

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