# Arrhythmia disease classification utilizing ResRNN

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/arrhythmia-disease-classification-utilizing-resrnn/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Shikha Dhyani,Adesh Kumar,Sushabhan Choudhury |
| Citations | 42 |
| DOI | 10.1016/j.bspc.2022.104160 |
| Fields | Medicine,Neuroscience |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4295332083 |
| Type | article |
| Year | 2022 |

## Paper authors

- [Sushabhan Choudhury](https://scholariq.org/researchers/sushabhan-choudhury/)

## Paper primary topic

- [ECG Monitoring and Analysis](https://scholariq.org/topics/ecg-monitoring-and-analysis/)

## Paper topics

- [ECG Monitoring and Analysis](https://scholariq.org/topics/ecg-monitoring-and-analysis/)
- [EEG and Brain-Computer Interfaces](https://scholariq.org/topics/eeg-and-brain-computer-interfaces/)
- [Cardiac electrophysiology and arrhythmias](https://scholariq.org/topics/cardiac-electrophysiology-and-arrhythmias/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.