Paper Citation Record · LEDGER

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction

As of 9 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2607.23412.

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2607.23412 v1

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measured 31 of 31 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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Outbound references

Observation 9de168d9-bfb0-4b7e-8f8c-21a4aeb1922e · outbound

This paper cites Development and Validation of Machine Learning Algorithms Based on Electrocardiograms for Cardiovascular Diagnoses at the Pop- ulation Level,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction Development and Validation of Machine Learning Algorithms Based on Electrocardiograms for Cardiovascular Diagnoses at the Pop- ulation Level,

Reference 1

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Observation 33b6abf7-f99b-4f8a-91c3-e8d1882d7be8 · outbound

This paper cites Towards Artificial Intelligence-Based Learning Health System for Population-Level Mortality Prediction Using Electrocardiograms,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction Towards Artificial Intelligence-Based Learning Health System for Population-Level Mortality Prediction Using Electrocardiograms,

Reference 2

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Observation 96f7bb3f-9a29-477f-8a42-8f7305d9f7ab · outbound

This paper cites Empirical investigation of multi-source cross-validation in clini- cal ECG classification,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction Empirical investigation of multi-source cross-validation in clini- cal ECG classification,

Reference 3

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Observation f6287739-62ea-4a82-b4db-91127acda051 · outbound

This paper cites Automatic Diagnosis of the 12-Lead ECG Using a Deep Neural Network,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction Automatic Diagnosis of the 12-Lead ECG Using a Deep Neural Network,

Reference 4

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Observation 0c9e9c98-dc75-46f4-bda1-5cc8acf847b8 · outbound

This paper cites Development and validation of machine learning algorithms based on electrocardiograms for cardiovascular diagnoses at the pop- ulation level,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction Development and validation of machine learning algorithms based on electrocardiograms for cardiovascular diagnoses at the pop- ulation level,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-30T23:02:38.313025Z

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Observation 4dc0fe7c-1823-47f5-ae60-be575f22495c · outbound

This paper cites ENCASE: An Ensemble Classifier for ECG Classification Using Expert Features and Deep Neural Networks,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction ENCASE: An Ensemble Classifier for ECG Classification Using Expert Features and Deep Neural Networks,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-30T23:02:38.406060Z

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Observation e74a143d-9f26-4533-85cf-45c3685477f7 · outbound

This paper cites Combining Deep Neural Networks and Engineered Features for Cardiac Arrhythmia Detection from ECG Recordings,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction Combining Deep Neural Networks and Engineered Features for Cardiac Arrhythmia Detection from ECG Recordings,

Reference 7

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Observation ccc3452b-91cc-482a-9561-549033ba110c · outbound

This paper cites Detecting Long QT Syndrome and First-Degree Atrioventricular Block Using Single-Lead AI-ECG: A Multi-Center Real-World Study,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction Detecting Long QT Syndrome and First-Degree Atrioventricular Block Using Single-Lead AI-ECG: A Multi-Center Real-World Study,

Reference 8

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Observation 0167b5f5-2ed1-4dac-b081-6a2a354daefb · outbound

This paper cites Evaluation of Handcrafted Features and Learned Representations for the Classification of Arrhythmia and Congestive Heart Failure in ECG,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction Evaluation of Handcrafted Features and Learned Representations for the Classification of Arrhythmia and Congestive Heart Failure in ECG,

Reference 9

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Observation d84bcf9e-bc15-4c74-8b74-4883af02d332 · outbound

This paper cites Cardiologist-Level Arrhythmia Detection and Classification in Ambulatory Electrocardiograms Using a Deep Neural Network,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction Cardiologist-Level Arrhythmia Detection and Classification in Ambulatory Electrocardiograms Using a Deep Neural Network,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-30T23:02:38.639985Z

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Observation dca96bd8-cd3f-46bb-89d4-ca63fd28ec18 · outbound

This paper cites Prospective validation of a deep learning electrocardio- gram algorithm for the detection of left ventricular systolic dysfunction,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction Prospective validation of a deep learning electrocardio- gram algorithm for the detection of left ventricular systolic dysfunction,

Reference 11

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Observation 86c1ac1a-965c-49c7-b092-147174db5322 · outbound

This paper cites Opportunities and challenges of deep learning methods for electrocardiogram data: A systematic review,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction Opportunities and challenges of deep learning methods for electrocardiogram data: A systematic review,

Reference 12

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Observation dd9cddfd-7d2f-4e0d-ba22-196f7df3df21 · outbound

This paper cites The Clinician and Dataset Shift in Artificial Intelligence,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction The Clinician and Dataset Shift in Artificial Intelligence,

Reference 13

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Observation 217da58e-06b8-4e95-ad0f-9cf4be98a61b · outbound

This paper cites Generalization challenges in electrocardiogram deep learning: insights from dataset characteristics and attention mech- anism,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction Generalization challenges in electrocardiogram deep learning: insights from dataset characteristics and attention mech- anism,

Reference 14

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Observation 5467a9f3-f75d-4cef-a9f7-bf132b2761be · outbound

This paper cites Heart rate variability: standards of measurement, physiological interpretation and clinical use,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction Heart rate variability: standards of measurement, physiological interpretation and clinical use,

Reference 15

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Observation 60036db0-df65-4104-9e1b-ab0422ea167e · outbound

This paper cites Recommendations for the Standardization and Inter- pretation of the Electrocardiogram,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction Recommendations for the Standardization and Inter- pretation of the Electrocardiogram,

Reference 16

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Observation 0768862f-ceb1-4ef2-a19b-dce182fcafaf · outbound

This paper cites AF classification from a short single lead ECG recording: The PhysioNet/Computing in Cardiology Challenge 2017,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction AF classification from a short single lead ECG recording: The PhysioNet/Computing in Cardiology Challenge 2017,

Reference 17

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Observation b8996bee-408e-48b5-b4b4-a7bd2326b316 · outbound

This paper cites Cardiac arrhythmia classifi- cation using autoregressive modeling,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction Cardiac arrhythmia classifi- cation using autoregressive modeling,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-30T23:02:39.161848Z

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Observation e4dbdb07-eb8e-4fb9-ae34-0a8ed9d653fd · outbound

This paper cites Combining low- dimensional wavelet features and support vector machine for arrhythmia beat classification,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction Combining low- dimensional wavelet features and support vector machine for arrhythmia beat classification,

Reference 19

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Observation 4ff01291-7de6-41a7-a71a-2eea951aed7e · outbound

This paper cites Calibration: the Achilles heel of predictive analytics,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction Calibration: the Achilles heel of predictive analytics,

Reference 20

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Observation 13c0012a-772f-4c7e-a6fb-70d268efd93e · outbound

This paper cites Changing predictor measurement procedures affected the performance of prediction models in clinical examples,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction Changing predictor measurement procedures affected the performance of prediction models in clinical examples,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-30T23:02:39.373677Z

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Observation d5bea358-ed41-4d10-abff-ffef1af474d7 · outbound

This paper cites Comparison of automated interval measurements by widely used algorithms in digital electrocardiographs,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction Comparison of automated interval measurements by widely used algorithms in digital electrocardiographs,

Reference 22

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Observation 0d238d17-ba10-46a4-b6a9-bea0658fa326 · outbound

This paper cites Research on cross- dataset cardiac signal domain generalization and feature interpretability,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction Research on cross- dataset cardiac signal domain generalization and feature interpretability,

Reference 23

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Observation c32e7731-9cb8-4801-b1a3-e38d3c8ce054 · outbound

This paper cites MIMIC-IV-ECG: Diagnostic Electrocardiogram Matched Subset,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction MIMIC-IV-ECG: Diagnostic Electrocardiogram Matched Subset,

Reference 24

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Observation d144e673-067b-4086-ae06-c18db69b26be · outbound

This paper cites Evaluation and management of athletes with long QT syndrome,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction Evaluation and management of athletes with long QT syndrome,

Reference 26

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Observation 0c9d8aa5-8bb6-4003-acd0-b6c4ef702e38 · outbound

This paper cites XGBoost: A Scalable Tree Boosting System,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction XGBoost: A Scalable Tree Boosting System,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-30T23:02:39.734498Z

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Observation 117d304e-8c1e-4490-91ec-1c1dcff0b236 · outbound

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Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction Unresolved cited work

Reference 28

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Observation d5cc8b42-803d-407a-879e-96a3f45bd8d9 · outbound

This paper cites an unresolved cited work.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction Unresolved cited work

Reference 29

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Observation 6a7b2e05-f871-447b-9609-1ef43b29e0ab · outbound

This paper cites A Unified Approach to Interpreting Model Predictions,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction A Unified Approach to Interpreting Model Predictions,

Reference 30

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Observation 5c3542e1-bb07-47cf-b5eb-d42b98807ded · outbound

This paper cites Optuna: A Next-Generation Hyperparameter Optimization Framework,.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction Optuna: A Next-Generation Hyperparameter Optimization Framework,

Reference 31

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This paper cites ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders.

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders

Reference 32

Resolution: unresolved; no resolver link, observed 2026-07-30T23:02:40.103651Z

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