Reference health
Adaptive Deep Reinforcement Learning Model for Predicting Arrhythmia from Ecg Signal
19/19 checkable references clean · checked 2026-07-23
Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.
9 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.
The 19 checked references that resolve
resolves10.1016/j.future.2018.03.057
A deep learning approach for ECG-based heartbeat classification for arrhythmia detection
resolves10.1016/j.compbiomed.2017.08.022
A deep convolutional neural network model to classify heartbeats
resolves10.1016/j.compbiomed.2018.05.013
A novel application of deep learning for single-lead ECG classification
resolves10.1016/j.procs.2018.05.034
Automated detection of cardiac arrhythmia using deep learning techniques
resolves10.1016/j.compbiomed.2018.03.016
A novel wavelet sequence based on deep bidirectional LSTM network model for ECG signal classification
resolves10.3390/rs12101685
Classification of Arrhythmia by Using Deep Learning with 2-D ECG Spectral Image Representation
resolves10.1006/cbmr.1994.1006
Automatic Detection of Wave Boundaries in Multilead ECG Signals: Validation with the CSE Database
resolves10.1109/ICASSP.2019.8683140
Inter- and Intra- Patient ECG Heartbeat Classification for Arrhythmia Detection: A Sequence to Sequence Deep Learning Approach
resolves10.1016/j.compbiomed.2018.06.002
Automated diagnosis of arrhythmia using combination of CNN and LSTM techniques with variable length heart beats
resolves10.1016/j.compbiomed.2018.09.009
Arrhythmia detection using deep convolutional neural network with long duration ECG signals
resolves10.1016/j.cmpb.2019.05.004
A new approach for arrhythmia classification using deep coded features and LSTM networks
resolves10.1109/ACCESS.2018.2833841
Automated ECG Classification Using Dual Heartbeat Coupling Based on Convolutional Neural Network
resolves10.3390/rs9111106
Detection of Informal Settlements from VHR Images Using Convolutional Neural Networks
resolves10.1109/TCYB.2020.2983860
Automatically Designing CNN Architectures Using the Genetic Algorithm for Image Classification
The 9 references without a DOI — listed, not checked
no DOI — not checkedref1
no DOI — not checkedSilent Atrial Fibrillation: A Critical Review
no DOI — not checkedref10
no DOI — not checkedClassification of ECG signals based on 1D convolution neural network
no DOI — not checkedref21
no DOI — not checkedref24
no DOI — not checkedref26
no DOI — not checkedref27
no DOI — not checkedref28
What this badge says. CiteStamped means the CHECKABLE references of this
work were clean at the dated check: each resolved to a known work in a public registry, and none
carried a retraction notice at that time. It says nothing about the quality, findings,
or importance of the work itself, and nothing about references deposited without a DOI.
checked 2026-07-23 — re-checked daily as this page is visited; titles and statuses come from Crossref and DataCite and are not part of the signed record
Embed this badge
Both snippets point at the live badge image and link back to this page. The badge re-renders from the daily check, so an embed never goes stale by more than a day of visits.
<a href="https://citestamp.com/citestamped/10.2139/ssrn.4069600"><img src="https://citestamp.com/citestamped/10.2139/ssrn.4069600/badge.svg" alt="CiteStamped reference-health badge" width="460" height="64"></a>
[](https://citestamp.com/citestamped/10.2139/ssrn.4069600)