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Defibrillators, Implantable

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Technical note: Minimizing CIED artifacts on a 0.35 T MRI-Linac using deep learning.

Journal of applied clinical medical physics 38368615
BACKGROUND: Artifacts from implantable cardioverter defibrillators (ICDs) are a challenge to magnetic resonance imaging (MRI)-guided radiotherapy (MRgRT).
Artifacts Deep Learning Defibrillators, Implantable Humans Image Processing, Computer-Assisted Magnetic Resonance Imaging Radiotherapy, Image-Guided
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Enhancing transvenous lead extraction risk prediction: Integrating imaging biomarkers into machine learning models.

Heart rhythm 38354872
BACKGROUND: Machine learning (ML) models have been proposed to predict risk related to transvenous lead extraction (TLE).
Aged Biomarkers Defibrillators, Implantable Device Removal Female Humans Machine Learning Male Middle Aged Neural Networks, Computer Retrospective Studies Risk Assessment Vena Cava, Superior
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Ethical use of artificial intelligence to prevent sudden cardiac death: an interview study of patient perspectives.

BMC medical ethics 38575931
BACKGROUND: The emergence of artificial intelligence (AI) in medicine has prompted the development of numerous ethical guidelines, while the involvement of patients in the creation of these documents lags behind. As part of the European PROFID projec...
Artificial Intelligence Death, Sudden, Cardiac Defibrillators, Implantable Delivery of Health Care Humans Qualitative Research
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Machine learning for prediction of ventricular arrhythmia episodes from intracardiac electrograms of automatic implantable cardioverter-defibrillators.

Heart rhythm 38797305
BACKGROUND: Despite effectiveness of the implantable cardioverter-defibrillator (ICD) in saving patients with life-threatening ventricular arrhythmias (VAs), the temporal occurrence of VA after ICD implantation is unpredictable.
Aged Defibrillators, Implantable Electrophysiologic Techniques, Cardiac Female Humans Machine Learning Male Middle Aged Predictive Value of Tests Registries Retrospective Studies Tachycardia, Ventricular Ventricular Fibrillation
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Future perspectives and challenges of artificial intelligence implementation in remote monitoring of cardiac implantable electronic devices.

Expert review of medical devices 39268946
Artificial Intelligence Defibrillators, Implantable Humans Monitoring, Physiologic Pacemaker, Artificial
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Open Access Data and Deep Learning for Cardiac Device Identification on Standard DICOM and Smartphone-based Chest Radiographs.

Radiology. Artificial intelligence 39017033
Purpose To develop and evaluate a publicly available deep learning model for segmenting and classifying cardiac implantable electronic devices (CIEDs) on Digital Imaging and Communications in Medicine (DICOM) and smartphone-based chest radiographs. M...
Adolescent Adult Aged Aged, 80 and over Deep Learning Defibrillators, Implantable Female Humans Male Middle Aged Pacemaker, Artificial Radiography, Thoracic Retrospective Studies Smartphone Young Adult
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Machine Learning-Based Prediction of Death and Hospitalization in Patients With Implantable Cardioverter Defibrillators.

Journal of the American College of Cardiology 39570241
BACKGROUND: Predicting the clinical trajectory of individual patients with implantable cardioverter-defibrillators (ICDs) is essential to inform clinical care. Machine learning approaches can potentially overcome the limitations of conventional stati...
Aged Defibrillators, Implantable Female Heart Failure Hospitalization Humans Machine Learning Male Middle Aged Risk Assessment
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Rhythm-Ready: Harnessing Smart Devices to Detect and Manage Arrhythmias.

Current cardiology reports 39422821
PURPOSE OF REVIEW: To survey recent progress in the application of implantable and wearable sensors to detection and management of cardiac arrhythmias.
Algorithms Arrhythmias, Cardiac Artificial Intelligence Defibrillators, Implantable Humans Wearable Electronic Devices
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Machine Learning-Based Clustering Using a 12-Lead Electrocardiogram in Patients With a Implantable Cardioverter Defibrillator to Identify Future Ventricular Arrhythmia.

Circulation journal : official journal of the Japanese Circulation Society 39358305
BACKGROUND: Implantable cardioverter defibrillators (ICDs) reduce mortality associated with ventricular arrhythmia in high-risk patients with cardiovascular disease. Machine learning (ML) approaches are promising tools in arrhythmia research; however...
Aged Arrhythmias, Cardiac Cluster Analysis Defibrillators, Implantable Electrocardiography Female Humans Machine Learning Male Middle Aged Retrospective Studies Tachycardia, Ventricular
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Active learning and margin strategies for arrhythmia classification in implantable devices.

Computers in biology and medicine 39951979
BACKGROUND AND OBJECTIVES: The massive storage of cardiac arrhythmic episodes from Implantable Cardioverter Defibrillators (ICD) and the advent of new artificial intelligence algorithms are opening up new opportunities for electrophysiological knowle...
Algorithms Arrhythmias, Cardiac Defibrillators, Implantable Humans Machine Learning Supervised Machine Learning
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