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Rutger R van de Leur

Showing results (1-10 of 25) with videos related to

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BMC Medical Research Methodology|October 28, 2019
Incorporating repeated measurements into prediction models in the critical care setting: a framework, systematic review and meta-analysisJoost D J Plate, Rutger R van de Leur, Luke P H Leenen, et al.
European Heart Journal. Digital Health|March 16, 2026
Signal or noise? Evaluating commonly used attribution methods for explaining deep neural networks in electrocardiogram classificationBauke K O Arends, Wouter A C van Amsterdam, Pim van der Harst, et al.
JMIR Cardio|July 7, 2023
Electrocardiogram Devices for Home Use: Technological and Clinical Scoping ReviewAlejandra Zepeda-Echavarria, Rutger R van de Leur, Meike van Sleuwen, et al.
Heart Rhythm|January 12, 2026
External validation of an explainable electrocardiogram-only deep learning algorithm for prediction of response after cardiac resynchronization therapyRutger R van de Leur, Derek J Bivona, Rohan Herur, et al.
Heliyon|January 15, 2025
Altered circadian rhythmicity of the QT interval predicts mortality in a large real-world academic hospital populationRutger R van de Leur, Bastiaan C du Pré, Markella I Printezi, et al.
European Heart Journal. Digital Health|January 24, 2024
Automatic triage of twelve-lead electrocardiograms using deep convolutional neural networks: a first implementation studyRutger R van de Leur, Meike T G M van Sleuwen, Peter-Paul M Zwetsloot, et al.
Journal of the American Heart Association|May 15, 2020
Automatic Triage of 12-Lead ECGs Using Deep Convolutional Neural NetworksRutger R van de Leur, Lennart J Blom, Efstratios Gavves, et al.
European Heart Journal. Digital Health|January 30, 2023
Uncertainty estimation for deep learning-based automated analysis of 12-lead electrocardiogramsJeroen F Vranken, Rutger R van de Leur, Deepak K Gupta, et al.
Npj Aging|March 21, 2026
Electrocardiogram derived heart age models agreement, accuracy and predictive ability in the Tromsø studyArya Panthalanickal Vijayakumar, Tom Wilsgaard, Henrik Schirmer, et al.
Iscience|August 18, 2025
Deep representation learning of electrocardiogram reveals biological insights in cardiac phenotypes and cardiovascular diseasesMing Wai Yeung, Rutger R van de Leur, Jan Walter Benjamins, et al.
Pageof 3

Showing results (1-10 of 25) with videos related to

Sort By:
Pageof 3
BMC Medical Research Methodology|October 28, 2019
Incorporating repeated measurements into prediction models in the critical care setting: a framework, systematic review and meta-analysisJoost D J Plate, Rutger R van de Leur, Luke P H Leenen, et al.
European Heart Journal. Digital Health|March 16, 2026
Signal or noise? Evaluating commonly used attribution methods for explaining deep neural networks in electrocardiogram classificationBauke K O Arends, Wouter A C van Amsterdam, Pim van der Harst, et al.
JMIR Cardio|July 7, 2023
Electrocardiogram Devices for Home Use: Technological and Clinical Scoping ReviewAlejandra Zepeda-Echavarria, Rutger R van de Leur, Meike van Sleuwen, et al.
Heart Rhythm|January 12, 2026
External validation of an explainable electrocardiogram-only deep learning algorithm for prediction of response after cardiac resynchronization therapyRutger R van de Leur, Derek J Bivona, Rohan Herur, et al.
Heliyon|January 15, 2025
Altered circadian rhythmicity of the QT interval predicts mortality in a large real-world academic hospital populationRutger R van de Leur, Bastiaan C du Pré, Markella I Printezi, et al.
European Heart Journal. Digital Health|January 24, 2024
Automatic triage of twelve-lead electrocardiograms using deep convolutional neural networks: a first implementation studyRutger R van de Leur, Meike T G M van Sleuwen, Peter-Paul M Zwetsloot, et al.
Journal of the American Heart Association|May 15, 2020
Automatic Triage of 12-Lead ECGs Using Deep Convolutional Neural NetworksRutger R van de Leur, Lennart J Blom, Efstratios Gavves, et al.
European Heart Journal. Digital Health|January 30, 2023
Uncertainty estimation for deep learning-based automated analysis of 12-lead electrocardiogramsJeroen F Vranken, Rutger R van de Leur, Deepak K Gupta, et al.
Npj Aging|March 21, 2026
Electrocardiogram derived heart age models agreement, accuracy and predictive ability in the Tromsø studyArya Panthalanickal Vijayakumar, Tom Wilsgaard, Henrik Schirmer, et al.
Iscience|August 18, 2025
Deep representation learning of electrocardiogram reveals biological insights in cardiac phenotypes and cardiovascular diseasesMing Wai Yeung, Rutger R van de Leur, Jan Walter Benjamins, et al.
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