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Conventional task-specific electrocardiogram (ECG) analysis models require large annotated datasets to train.
“PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals”
A.. Goldberger et al · 2000
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“ACC/AHA Clinical Competence Statement on Electrocardiography and Ambulatory Electrocardiography”
Alan. Kadish et al · 2001
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“Adam: A Method for Stochastic Optimization”, 2017
Diederik. Kingma and Jimmy Ba · 2017
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“Screening for cardiac contractile dysfunction using an artificial intelligence–enabled electrocardiogram”
Zachi. Attia et al · 2019
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“Accuracy of Physicians’ Electrocardiogram Interpretations: A Systematic Review and Meta-analysis”
D.. Cook, S.. Oh and M.. Pusic · 2020
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“wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations”
Alexei Baevski, Yuhao Zhou, Abdelrahman Mohamed and Michael Auli · 2020
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“Heart Failure With Reduced Ejection Fraction: A Review”
Sean. Murphy, Nasrien. Ibrahim and Jr. Januzzi James · 2020
Earlier work this paper cites.
“ECG AI-Guided Screening for Low Ejection Fraction (EAGLE): Rationale and design of a pragmatic cluster randomized trial”
Xiaoxi Yao et al · 2020
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“ECG Interpretation: Clinical Relevance, Challenges, and Advances”
Nikita Rafie, Anthony. Kashou and Peter. Noseworthy · 2021
Earlier work this paper cites.
“Med-BERT: pretrained contextualized embeddings on large-scale structured electronic health records for disease prediction”
Laila Rasmy et al · 2021
Earlier work this paper cites.
“CLOCS: Contrastive Learning of Cardiac Signals Across Space, Time, and Patients”
Dani Kiyasseh, Tingting Zhu and David Clifton · 2021
Earlier work this paper cites.
“Time-series representation learning via temporal and contextual contrasting”
Emadeldeen Eldele et al · 2021
Earlier work this paper cites.
“Will Two Do? Varying Dimensions in Electrocardiography: The PhysioNet/Computing in Cardiology Challenge 2021”
Matthew Reyna et al · 2021
Cited alongside, same era.
“Artificial intelligence–enabled electrocardiograms for identification of patients with low ejection fraction: a pragmatic, randomized clinical trial”
Xiaoxi Yao et al · 2021
Cited alongside, same era.
“Artificial intelligence-guided screening for atrial fibrillation using electrocardiogram during sinus rhythm: a prospective non-randomised interventional trial”
P.. Noseworthy et al · 2022
Cited alongside, same era.
“Artificial intelligence versus physicians on interpretation of printed ECG images: Diagnostic performance of ST-elevation myocardial infarction on electrocardiography”
Yoo Choi et al · 2022
Cited alongside, same era.
“Lead-agnostic Self-supervised Learning for Local and Global Representations of Electrocardiogram”
Jungwoo Oh et al · 2022
“A foundational vision transformer improves diagnostic performance for electrocardiograms”
Akhil Vaid et al · 2023
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“Improving pixel-based mim by reducing wasted modeling capability”
Yuan Liu et al · 2023
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“Adversarial spatiotemporal contrastive learning for electrocardiogram signals”
Ning Wang et al · 2023
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“MIMIC-IV, a freely accessible electronic health record dataset”
Alistair.. Johnson et al · 2023
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“Improving generalization performance of electrocardiogram classification models”
Hyeongrok Han et al · 2023
Later among the works it cites.
“Validation of an automated artificial intelligence system for 12 -
Robert Herman et al · 2024
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Cited alongside, same era.
“Will Two Do? Varying Dimensions in Electrocardiography: The PhysioNet/Computing in Cardiology Challenge 2021”
Matthew Reyna et al · 2022
Cited alongside, same era.
“Classification of ECG using ensemble of residual CNNs with or without attention mechanism”
Petr Nejedly et al · 2022
Cited alongside, same era.
“Blinded, randomized trial of sonographer versus AI cardiac function assessment”
Bryan He et al · 2023
Cited alongside, same era.
“International evaluation of an artificial intelligence–powered electrocardiogram model detecting acute coronary occlusion myocardial infarction”
Robert Herman et al · 2023
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“Machine learning for ECG diagnosis and risk stratification of occlusion myocardial infarction”
Salah. Al-Zaiti et al · 2023
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“Clinical Camel: An Open Expert-Level Medical Language Model with Dialogue-Based Knowledge Encoding”
Augustin Toma et al · 2023
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“ECGBERT: Understanding Hidden Language of ECGs with Self-Supervised Representation Learning”
Seokmin Choi et al · 2023
Cited alongside, same era.
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Jun Ma et al · 2024
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