Paper Citation Record · LEDGER

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection

As of 23 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:1908.06857.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1908.06857 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T14:22:09.614914Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

26 of 26 outbound references displayed

verified exact0
verified fuzzy26
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 22c44998-bb6b-48df-830e-1f3f4af23024 · outbound

This paper cites Comparing feature-based clas- siﬁers and convolutional neural networks to detect arrhyth- mia from short segments of ecg.

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection Comparing feature-based clas- siﬁers and convolutional neural networks to detect arrhyth- mia from short segments of ecg

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:22:10.062829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a182bf4f-0843-4902-a809-221686a6ab05 · outbound

This paper cites Af classiﬁcation from a short sin- gle lead ecg recording: the physionet/computing in cardi- ology challenge.

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection Af classiﬁcation from a short sin- gle lead ecg recording: the physionet/computing in cardi- ology challenge

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:22:10.007395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 44fb551e-14ce-447a-819b-f38be752edab · outbound

This paper cites Real-time ecg monitoring and arrhythmia detection using android-based mobile devices.

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection Real-time ecg monitoring and arrhythmia detection using android-based mobile devices

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:22:09.989218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b4a31178-31f2-47a2-b903-baf996ed5185 · outbound

This paper cites Combining deep neural networks and engineered fea- tures for cardiac arrhythmia detection from ECG record- ings.

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection Combining deep neural networks and engineered fea- tures for cardiac arrhythmia detection from ECG record- ings

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:22:09.926560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e859179d-4627-4f00-aa9e-af785e3df806 · outbound

This paper cites Atrial ﬁbrillation detection using feedforward neural networks and automatically extracted signal features.

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection Atrial ﬁbrillation detection using feedforward neural networks and automatically extracted signal features

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:22:09.909710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2540d079-7286-4e2e-83ed-fa9c81e26e9c · outbound

This paper cites A robust deep convolutional neural network for the classiﬁcation of abnormal cardiac rhythm using single lead electrocardio- grams of variable length.

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection A robust deep convolutional neural network for the classiﬁcation of abnormal cardiac rhythm using single lead electrocardio- grams of variable length

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:22:09.893699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3c96f7df-00cc-4d8d-b7c2-402d754b3033 · outbound

This paper cites Accurate, automated detec- tion of atrial ﬁbrillation in ambulatory recordings.

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection Accurate, automated detec- tion of atrial ﬁbrillation in ambulatory recordings

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:22:09.846993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 194eb6b2-2a5b-45f6-aaaf-0e9775df11e5 · outbound

This paper cites Robust greedy deep dictionary learning for ecg arrhythmia classiﬁcation.

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection Robust greedy deep dictionary learning for ecg arrhythmia classiﬁcation

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:22:09.831496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6751ede5-ab99-4df0-9b79-a714e0a3da3a · outbound

This paper cites Beat by beat: Classifying cardiac ar- rhythmias with recurrent neural networks.

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection Beat by beat: Classifying cardiac ar- rhythmias with recurrent neural networks

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:22:09.816416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1b17c277-8ac7-4dc8-b68b-5aa113eb3da4 · outbound

This paper cites Errors in the computerized electrocardiogram inter- pretation of cardiac rhythm.

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection Errors in the computerized electrocardiogram inter- pretation of cardiac rhythm

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:22:09.801852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0a149800-4f21-45c9-a4a6-93eb8f06dae7 · outbound

This paper cites Classiﬁcation of ecg recordings with neu- ral networks based on speciﬁc morphological features and regularity of the signal.

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection Classiﬁcation of ecg recordings with neu- ral networks based on speciﬁc morphological features and regularity of the signal

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:22:09.754258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5e8cc6f5-7193-4897-8a02-45452354b592 · outbound

This paper cites Automatic detection of atrial ﬁbrillation using the coefﬁcient of varia- tion and density histograms of rr andδrr intervals.

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection Automatic detection of atrial ﬁbrillation using the coefﬁcient of varia- tion and density histograms of rr andδrr intervals

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:22:09.737616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation cf67a5e3-745a-4d4f-b97a-00ab6320ceff · outbound

This paper cites A novel method for classiﬁcation of ecg arrhythmias using deep belief networks.

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection A novel method for classiﬁcation of ecg arrhythmias using deep belief networks

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:22:09.701709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation cc6faf73-7654-4217-80b1-1c0052bdad5c · outbound

This paper cites Robust ecg signal classiﬁcation for detec- tion of atrial ﬁbrillation using a novel neural network.

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection Robust ecg signal classiﬁcation for detec- tion of atrial ﬁbrillation using a novel neural network

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:22:09.685696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f2727335-f958-4e20-80aa-8a987af6c1e8 · outbound

This paper cites Arrhythmia detection and classiﬁ- cation using morphological and dynamic features of ecg signals.

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection Arrhythmia detection and classiﬁ- cation using morphological and dynamic features of ecg signals

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:22:09.669997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 357a0dba-413d-4b1f-b113-5e0a302008e0 · outbound

This paper cites Ensembling convolutional and long short-term memory networks for electrocardio- gram arrhythmia detection.

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection Ensembling convolutional and long short-term memory networks for electrocardio- gram arrhythmia detection

Reference 2001

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:22:09.718309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9f745403-416c-400c-b2d3-2f8c12b8f60f · outbound

This paper cites Real-time patient-speciﬁc ecg classiﬁ- cation by 1-d convolutional neural networks.

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection Real-time patient-speciﬁc ecg classiﬁ- cation by 1-d convolutional neural networks

Reference 2005

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:22:09.863071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8a52efe2-885b-4874-8115-c74a34e882ac · outbound

This paper cites Improving the quality of ecgs collected using mobile phones: The physionet/computing in cardiology challenge.

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection Improving the quality of ecgs collected using mobile phones: The physionet/computing in cardiology challenge

Reference 2007

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:22:09.786128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7e2008e0-42f8-4fdb-a6e4-be087d9a59a8 · outbound

This paper cites Convolu- tional recurrent neural networks for electrocardiogram classiﬁcation.

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection Convolu- tional recurrent neural networks for electrocardiogram classiﬁcation

Reference 2010

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:22:09.653528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5a96fdd9-67d7-48f0-8ddd-643a64e8b081 · outbound

This paper cites A convolutional neural network for ecg annotation as the basis for classiﬁcation of cardiac rhythms.

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection A convolutional neural network for ecg annotation as the basis for classiﬁcation of cardiac rhythms

Reference 2011

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:22:09.770206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 691ef48a-9a51-45c3-a16f-3fb1910ca180 · outbound

This paper cites Cardiologist-level ar- rhythmia detection and classiﬁcation in ambulatory elec- trocardiograms using a deep neural network.

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection Cardiologist-level ar- rhythmia detection and classiﬁcation in ambulatory elec- trocardiograms using a deep neural network

Reference 2012

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:22:09.973643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7cf36bfb-5a0a-4662-9899-e4e00a1c3bdf · outbound

This paper cites Atrial ﬁbrillation detection using con- volutional neural networks.

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection Atrial ﬁbrillation detection using con- volutional neural networks

Reference 2015

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:22:10.029125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 24505de4-b25f-4285-8bb1-5076f9511b80 · outbound

This paper cites Encase: An ensemble classiﬁer for ecg classiﬁcation using expert features and deep neural networks.

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection Encase: An ensemble classiﬁer for ecg classiﬁcation using expert features and deep neural networks

Reference 2016

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:22:09.942465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a64d7604-18f2-4a10-8468-b0d655d4d422 · outbound

This paper cites Heart rate dynamics distinguish among atrial ﬁbrillation, normal sinus rhythm and sinus rhythm with frequent ectopy.

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection Heart rate dynamics distinguish among atrial ﬁbrillation, normal sinus rhythm and sinus rhythm with frequent ectopy

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:22:10.046504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0f389bd6-2d7e-414d-8feb-49059df48a0c · outbound

This paper cites Basis and treatment of cardiac arrhythmias , vol- ume.

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection Basis and treatment of cardiac arrhythmias , vol- ume

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:22:09.878716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b4442391-2405-4ccf-aaf7-d7048c707453 · outbound

This paper cites Deep residual learning for image recogni- tion.

K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection Deep residual learning for image recogni- tion

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:22:09.958173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

No inbound Pith citation observations are available.