Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification | Paper Citation Record

Observation 1d1481a9-1b43-4973-a158-df8e80aab391 · outbound

This paper cites A Systematic Review of Time Series Classification Techniques Used in Biomedical Applications,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification A Systematic Review of Time Series Classification Techniques Used in Biomedical Applications,

Reference 1

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Observation 7ca9078d-1e6d-4b1b-aef8-7d8b24298e45 · outbound

This paper cites Ethical Challenges Posed by Big Data,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Ethical Challenges Posed by Big Data,

Reference 2

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Observation 0036795b-ddd1-4273-9c93-3d87a317770f · outbound

This paper cites Biomedical Data Sharing and Reuse: Attitudes and Practices of Clinical and Scientific Research Staff,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Biomedical Data Sharing and Reuse: Attitudes and Practices of Clinical and Scientific Research Staff,

Reference 3

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Observation 502a6d0c-5c65-4c82-8293-d1a2306dda4c · outbound

This paper cites Handling limited datasets with neural networks in medical appli- cations: A small-data approach,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Handling limited datasets with neural networks in medical appli- cations: A small-data approach,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:26.088842Z

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Observation 513cd5a7-221a-4baf-9b72-1ca6aa4ebefd · outbound

This paper cites Commentary: The Problem of Class Imbalance in Biomedical Data,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Commentary: The Problem of Class Imbalance in Biomedical Data,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:26.079068Z

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Observation bc448be0-3c62-4c44-8310-f99895b6e028 · outbound

This paper cites Data Augmentation techniques in time series domain: A survey and taxonomy.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Data Augmentation techniques in time series domain: A survey and taxonomy

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-12T11:15:25.559136Z

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Observation b027d1fb-1e9b-471f-8b2e-64d5d5fbac29 · outbound

This paper cites On the Challenges and Opportunities in Generative AI,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification On the Challenges and Opportunities in Generative AI,

Reference 7

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Observation 59dab44c-cdfa-4225-aa6d-a4412d885ce0 · outbound

This paper cites Deep generative modelling: A comparative review of vaes, gans, normalizing flows, energy-based and autoregressive models,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Deep generative modelling: A comparative review of vaes, gans, normalizing flows, energy-based and autoregressive models,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:26.058441Z

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Observation fc57ef72-3c24-49ae-b1ed-de04e7b853b9 · outbound

This paper cites A review on generative adversarial networks: Algorithms, the- ory, and applications,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification A review on generative adversarial networks: Algorithms, the- ory, and applications,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:26.047816Z

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Observation 6f333de1-33fa-465b-9a7a-b48bcafe931a · outbound

This paper cites Autoregressive models: What are they good for?,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Autoregressive models: What are they good for?,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:26.037920Z

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Observation 86c25106-2841-48c3-bdbd-525d7c5df8ef · outbound

This paper cites Normalizing flows for probabilistic modeling and inference,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Normalizing flows for probabilistic modeling and inference,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:26.028452Z

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Observation 792196f0-5aeb-423e-9f17-83337839cae2 · outbound

This paper cites Diffusion models: A comprehensive survey of methods and applica- tions,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Diffusion models: A comprehensive survey of methods and applica- tions,

Reference 12

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Observation 4a8c98a1-1d61-46b8-90ed-ecaf4ab2e710 · outbound

This paper cites Auto-encoding variational bayes,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Auto-encoding variational bayes,

Reference 13

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This paper cites Generative adversarial networks,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Generative adversarial networks,

Reference 14

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Observation b7c421a3-52ed-43c1-8ad1-4966e31cefbe · outbound

This paper cites Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity: dependence on recording region and brain state,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity: dependence on recording region and brain state,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:26.007742Z

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Observation 25884f00-dded-4b61-8959-345c5df97306 · outbound

This paper cites Stock Market Analysis Using Time Series Relational Models for Stock Price Prediction,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Stock Market Analysis Using Time Series Relational Models for Stock Price Prediction,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.997544Z

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Observation c95c5e77-b8cf-4f55-851c-8d328b883409 · outbound

This paper cites Time Series Prediction in Industry 4.0: A Com- prehensive Review and Prospects for Future Advancements,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Time Series Prediction in Industry 4.0: A Com- prehensive Review and Prospects for Future Advancements,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.987734Z

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Observation 9629d3c4-2603-493b-8c3d-ba6524717c6f · outbound

This paper cites Trend analysis of climate time series: A review of methods,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Trend analysis of climate time series: A review of methods,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.968964Z

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Observation b51624c7-959b-4342-aeb2-016bd9d7403a · outbound

This paper cites Characterizing parking systems from sensor data through a data-driven approach,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Characterizing parking systems from sensor data through a data-driven approach,

Reference 19

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Observation b6c2c995-fb0c-448f-af67-c88a27a3b5b0 · outbound

This paper cites Electrocardiogram generation with a bidirectional LSTM- CNN generative adversarial network,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Electrocardiogram generation with a bidirectional LSTM- CNN generative adversarial network,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.959589Z

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Observation de0bc9a4-9a8c-4c30-9213-df786565bf51 · outbound

This paper cites Quick and Easy Time Series Generation with Established Image-based GANs.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Quick and Easy Time Series Generation with Established Image-based GANs

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-12T11:15:25.414190Z

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Observation e05dc6c9-fc0d-4016-85e6-548098bf25a2 · outbound

This paper cites Synthesis of Realistic ECG using Generative Adversarial Networks.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Synthesis of Realistic ECG using Generative Adversarial Networks

Reference 22

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Observation c16226e8-6045-41a1-8d27-40f8757347db · outbound

This paper cites Pgans: Personalized generative adversarial networks for ecg synthesis to improve patient-specific deep ecg classification,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Pgans: Personalized generative adversarial networks for ecg synthesis to improve patient-specific deep ecg classification,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.949620Z

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Observation 49dde406-a988-4606-bcd0-4f81dab0d716 · outbound

This paper cites ECG Arrhythmias Detection Using Auxiliary Classifier Gen- erative Adversarial Network and Residual Network,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification ECG Arrhythmias Detection Using Auxiliary Classifier Gen- erative Adversarial Network and Residual Network,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.939965Z

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Observation 2a684db2-3d85-4f84-8521-2961044230c9 · outbound

This paper cites Investigating Deep Convolution Conditional GANs for Electrocardio- gram Generation,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Investigating Deep Convolution Conditional GANs for Electrocardio- gram Generation,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.930724Z

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Observation 007401f5-65ea-4198-a79f-81fa1ecad8b6 · outbound

This paper cites ECG signal generation based on conditional generative models,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification ECG signal generation based on conditional generative models,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.920487Z

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Observation 546e35fb-4fed-4178-a891-6284457d4293 · outbound

This paper cites Synthetic ECG Signal Generation Using Proba- bilistic Diffusion Models,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Synthetic ECG Signal Generation Using Proba- bilistic Diffusion Models,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.911323Z

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Observation 5b4543e7-a896-4609-b155-14e9b4ec1c4e · outbound

This paper cites Synthesis of standard 12-lead electrocardiograms using two- dimensional generative adversarial networks,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Synthesis of standard 12-lead electrocardiograms using two- dimensional generative adversarial networks,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.901427Z

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Observation 81bf7c0e-1ed1-49d1-9b30-f3dd7512a5db · outbound

This paper cites PTB-XL, a large publicly available electrocardiography dataset,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification PTB-XL, a large publicly available electrocardiography dataset,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.891197Z

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Observation 03f88967-058e-4749-94db-5989a73b8947 · outbound

This paper cites Chinese Cardiovascular Disease Database (CCDD) and Its Management Tool,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Chinese Cardiovascular Disease Database (CCDD) and Its Management Tool,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.881639Z

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Observation 1ad539da-a262-4cbd-864d-f361eb4597ed · outbound

This paper cites A 12-lead electrocardiogram database for arrhythmia research covering more than 10,000 patients,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification A 12-lead electrocardiogram database for arrhythmia research covering more than 10,000 patients,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.871449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a82ae4ee-4397-46db-a297-6efbbf9ae8ba · outbound

This paper cites Deepfake electrocardiograms using generative adver- sarial networks are the beginning of the end for privacy issues in medicine,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Deepfake electrocardiograms using generative adver- sarial networks are the beginning of the end for privacy issues in medicine,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.861493Z

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Observation a4b41448-d6da-4070-bc3c-642b817ab0b6 · outbound

This paper cites Multivariate Generative Adversarial Networks and Their Loss Functions for Synthesis of Multichannel ECGs,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Multivariate Generative Adversarial Networks and Their Loss Functions for Synthesis of Multichannel ECGs,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.851593Z

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Observation ca490dc5-7add-46bd-b127-ba6667bb18fe · outbound

This paper cites TTS-CGAN: A Transformer Time-Series Conditional GAN for Biosignal Data Augmentation.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification TTS-CGAN: A Transformer Time-Series Conditional GAN for Biosignal Data Augmentation

Reference 34

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Observation 5ab7b65b-2f36-4400-a4fc-442c154bf128 · outbound

This paper cites Diffusion-based conditional ECG generation with structured state space models,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Diffusion-based conditional ECG generation with structured state space models,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.833980Z

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Observation 46266f9e-771a-41a7-94c3-8e1ebfe92da9 · outbound

This paper cites ECG Synthesis via Diffusion-Based State Space Augmented Trans- former,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification ECG Synthesis via Diffusion-Based State Space Augmented Trans- former,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.824789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 459d8dc4-1351-4f8c-822b-040d41fac275 · outbound

This paper cites Automatic classification of heartbeats using ECG mor- phology and heartbeat interval features,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Automatic classification of heartbeats using ECG mor- phology and heartbeat interval features,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.814587Z

Source-reported events for the cited work

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Observation 5aec5c62-4547-45d1-9762-f0cf2a272535 · outbound

This paper cites Support vector machine-based expert system for reliable heartbeat recognition,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Support vector machine-based expert system for reliable heartbeat recognition,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.805472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 56c25a17-1356-4139-9326-bec20f944918 · outbound

This paper cites ECG arrhythmia classification based on optimum-path forest,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification ECG arrhythmia classification based on optimum-path forest,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.795349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d9978e31-5f8c-44a6-ac57-42191ca7c6f3 · outbound

This paper cites Electrocardiogram Classifica- tion Using Reservoir Computing With Logistic Regression,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Electrocardiogram Classifica- tion Using Reservoir Computing With Logistic Regression,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.785741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7a66719f-9b4a-4eb7-a07f-e8f692a33bfa · outbound

This paper cites Patient-Specific ECG Classification Based on Recurrent Neural Networks and Clustering Technique,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Patient-Specific ECG Classification Based on Recurrent Neural Networks and Clustering Technique,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.775379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c7135eef-0e43-4462-be91-f341df4fcb57 · outbound

This paper cites Automated detection of atrial fibrillation using long short-term memory network with RR interval signals,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Automated detection of atrial fibrillation using long short-term memory network with RR interval signals,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.766272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 01cda072-b43e-4546-85d9-2f4fd593bff8 · outbound

This paper cites Multiclass classification of myocardial infarction with convolutional and recurrent neural networks for portable ECG devices,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Multiclass classification of myocardial infarction with convolutional and recurrent neural networks for portable ECG devices,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.757039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 739d76d8-37dd-468c-bbec-d343388e0402 · outbound

This paper cites A deep learning approach for ECG-based heartbeat classification for arrhythmia detection,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification A deep learning approach for ECG-based heartbeat classification for arrhythmia detection,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.747644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e076c1bf-d70f-40d3-b097-c68d3c5b118a · outbound

This paper cites Automatic QRS complex detection using two-level convolutional neural network,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Automatic QRS complex detection using two-level convolutional neural network,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.737763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f99875b1-f1d9-4f3f-ab43-9c6845692209 · outbound

This paper cites Automated arrhythmia classification based on a com- bination network of CNN and LSTM,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Automated arrhythmia classification based on a com- bination network of CNN and LSTM,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.728922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e838b178-f51c-4871-862d-e1f065892389 · outbound

This paper cites DeepArrNet: An Efficient Deep CNN Architecture for Au- tomatic Arrhythmia Detection and Classification From Denoised ECG Beats,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification DeepArrNet: An Efficient Deep CNN Architecture for Au- tomatic Arrhythmia Detection and Classification From Denoised ECG Beats,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.719527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9723d54a-11e1-4bc8-bfec-0426b0ac48db · outbound

This paper cites Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-12T11:15:25.267463Z

Source-reported events for the cited work

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Observation 8d0b60a7-d4c7-4cdd-b95e-df8a622446e6 · outbound

This paper cites The impact of the MIT-BIH Arrhythmia Database,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification The impact of the MIT-BIH Arrhythmia Database,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.710211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d8b0991a-a737-4c4a-8b20-485bbc716910 · outbound

This paper cites An Open Access Database for Evaluating the Algorithms of Electrocardiogram Rhythm and Morphology Abnormality Detection,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification An Open Access Database for Evaluating the Algorithms of Electrocardiogram Rhythm and Morphology Abnormality Detection,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.700557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 601099ce-8e15-4c79-a91f-4ce4ed4d71bc · outbound

This paper cites Deep Learning- Based ECG Arrhythmia Classification: A Systematic Review,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Deep Learning- Based ECG Arrhythmia Classification: A Systematic Review,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.691093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 11bf6d7e-3f06-4048-8af8-c671b295b71f · outbound

This paper cites Deep learning for ECG Arrhythmia detection and classification: an overview of progress for period 2017–2023,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Deep learning for ECG Arrhythmia detection and classification: an overview of progress for period 2017–2023,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.671405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7730a633-ac80-4c68-83d1-166e0dbe33be · outbound

This paper cites A 12-lead electrocardiogram database for arrhythmia research covering more than 10,000 patients,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification A 12-lead electrocardiogram database for arrhythmia research covering more than 10,000 patients,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.660850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 300f0284-42ca-4ba0-96a9-5e59fbc3cecc · outbound

This paper cites an unresolved cited work.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Unresolved cited work

Reference 54

Resolution: unresolved; raw_fallback, observed 2026-08-12T11:15:25.681314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 91d45994-1f57-4a86-805f-c6edce685fd1 · outbound

This paper cites Diffusion-TS: Interpretable Diffusion for General Time Series Generation.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Diffusion-TS: Interpretable Diffusion for General Time Series Generation

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-12T11:15:25.293913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4fc29da-c707-459d-899b-926b3bb1263b · outbound

This paper cites U-net: Convolutional networks for biomedical image segmen- tation,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification U-net: Convolutional networks for biomedical image segmen- tation,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.651063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 46a7afba-be16-4027-b691-e0933782f472 · outbound

This paper cites DiffWave: A Versatile Diffusion Model for Audio Synthesis.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification DiffWave: A Versatile Diffusion Model for Audio Synthesis

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-12T11:15:25.289734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab4b2490-cdfa-4eb3-b8af-3b9694ee5a63 · outbound

This paper cites Neural discrete representation learning,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Neural discrete representation learning,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.630528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8d853d98-288e-48ec-8875-964d0529a6f6 · outbound

This paper cites Time Series Classification from Scratch with Deep Neural Networks: A Strong Baseline.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Time Series Classification from Scratch with Deep Neural Networks: A Strong Baseline

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-12T11:15:25.306737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40c5ffd6-eb05-4d94-a570-d6bbbe2d1d27 · outbound

This paper cites Vector quantized time series generation with a bidirectional prior model,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Vector quantized time series generation with a bidirectional prior model,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.640411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0df2591b-691c-4cd5-ab19-38e8086f8598 · outbound

This paper cites GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilib- rium,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilib- rium,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.611665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation deb5982e-a5ae-463e-b36b-1bd23f8c707c · outbound

This paper cites MMD GAN: Towards Deeper Understanding of Moment Matching Network,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification MMD GAN: Towards Deeper Understanding of Moment Matching Network,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.601272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation af3ae170-91df-46a1-b7ff-9224f1a8b223 · outbound

This paper cites Optuna: A next-generation hyperparameter op- timization framework,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Optuna: A next-generation hyperparameter op- timization framework,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.621101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2a2b5b1f-7522-49b1-b369-25d516089577 · outbound

This paper cites Umap: Uniform manifold approximation and pro- jection,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Umap: Uniform manifold approximation and pro- jection,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.585973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6ff6b744-7687-4159-82e7-71272d39d51b · outbound

This paper cites Understanding how dimension reduction tools work: An empirical approach to deciphering t-sne, umap, trimap, and pacmap for data visualization,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Understanding how dimension reduction tools work: An empirical approach to deciphering t-sne, umap, trimap, and pacmap for data visualization,

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-12T11:15:25.326857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70c18a6f-13a1-4b84-93d6-8f1d82b01904 · outbound

This paper cites Visualizing data using t-sne,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Visualizing data using t-sne,

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-12T11:15:25.320256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e47bc722-d857-4cf0-84c7-2df2f1d79255 · outbound

This paper cites Monitoring ai-modified content at scale: A case study on the impact of chatgpt on ai conference peer reviews,.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Monitoring ai-modified content at scale: A case study on the impact of chatgpt on ai conference peer reviews,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:15:25.570007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 09939c96-7909-40e9-be0e-b1b836e33f2b · outbound

This paper cites an unresolved cited work.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Unresolved cited work

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-12T11:15:25.218929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f8c8c28-4284-47ee-951c-a52d42111930 · outbound

This paper cites an unresolved cited work.

Synthetic ECG Generation for Data Augmentation and Transfer Learning in Arrhythmia Classification Unresolved cited work

Reference 2023

Resolution: unresolved; raw_fallback, observed 2026-08-12T11:15:25.978415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers