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Dewar Finlay

Showing results (41-50 of 48) with videos related to

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JMIR Medical Informatics|April 16, 2021
Reliable Deep Learning-Based Detection of Misplaced Chest Electrodes During Electrocardiogram Recording: Algorithm Development and ValidationKhaled Rjoob, Raymond Bond, Dewar Finlay, et al.
Journal of Electrocardiology|September 1, 2020
Machine learning techniques for detecting electrode misplacement and interchanges when recording ECGs: A systematic review and meta-analysisKhaled Rjoob, Raymond Bond, Dewar Finlay, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|November 16, 2007
HomeCI--a visual editor for healthcare professionals in the design of home based careChris D Nugent, Richard J Davies, Josef Hallberg, et al.
Journal of Electrocardiology|September 3, 2019
Data driven feature selection and machine learning to detect misplaced V1 and V2 chest electrodes when recording the 12‑lead electrocardiogramKhaled Rjoob, Raymond Bond, Dewar Finlay, et al.
European Heart Journal. Digital Health|January 30, 2023
The effect of confounding data features on a deep learning algorithm to predict complete coronary occlusion in a retrospective observational settingRob Brisk, Raymond Bond, Dewar Finlay, et al.
Artificial Intelligence in Medicine|October 7, 2022
Machine learning and the electrocardiogram over two decades: Time series and meta-analysis of the algorithms, evaluation metrics and applicationsKhaled Rjoob, Raymond Bond, Dewar Finlay, et al.
Journal of Electrocardiology|August 21, 2018
Automation bias in medicine: The influence of automated diagnoses on interpreter accuracy and uncertainty when reading electrocardiogramsRaymond R Bond, Tomas Novotny, Irena Andrsova, et al.
JMIR Research Protocols|October 30, 2025
Artificial Intelligence-Assisted Image Extraction in Neonatal Echocardiography for Congenital Heart Disease Diagnosis in Sub-Saharan Africa: Protocol for Model DevelopmentAminkeng Zawuo Leke, Lionel Landry Sop Deffo, Yunkavi Sabastian Wirsiy, et al.
Pageof 5

Showing results (41-50 of 48) with videos related to

Sort By:
Pageof 5
You have reached the last page of results.This site can display upto 48 results.
JMIR Medical Informatics|April 16, 2021
Reliable Deep Learning-Based Detection of Misplaced Chest Electrodes During Electrocardiogram Recording: Algorithm Development and ValidationKhaled Rjoob, Raymond Bond, Dewar Finlay, et al.
Journal of Electrocardiology|September 1, 2020
Machine learning techniques for detecting electrode misplacement and interchanges when recording ECGs: A systematic review and meta-analysisKhaled Rjoob, Raymond Bond, Dewar Finlay, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|November 16, 2007
HomeCI--a visual editor for healthcare professionals in the design of home based careChris D Nugent, Richard J Davies, Josef Hallberg, et al.
Journal of Electrocardiology|September 3, 2019
Data driven feature selection and machine learning to detect misplaced V1 and V2 chest electrodes when recording the 12‑lead electrocardiogramKhaled Rjoob, Raymond Bond, Dewar Finlay, et al.
European Heart Journal. Digital Health|January 30, 2023
The effect of confounding data features on a deep learning algorithm to predict complete coronary occlusion in a retrospective observational settingRob Brisk, Raymond Bond, Dewar Finlay, et al.
Artificial Intelligence in Medicine|October 7, 2022
Machine learning and the electrocardiogram over two decades: Time series and meta-analysis of the algorithms, evaluation metrics and applicationsKhaled Rjoob, Raymond Bond, Dewar Finlay, et al.
Journal of Electrocardiology|August 21, 2018
Automation bias in medicine: The influence of automated diagnoses on interpreter accuracy and uncertainty when reading electrocardiogramsRaymond R Bond, Tomas Novotny, Irena Andrsova, et al.
JMIR Research Protocols|October 30, 2025
Artificial Intelligence-Assisted Image Extraction in Neonatal Echocardiography for Congenital Heart Disease Diagnosis in Sub-Saharan Africa: Protocol for Model DevelopmentAminkeng Zawuo Leke, Lionel Landry Sop Deffo, Yunkavi Sabastian Wirsiy, et al.
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