AI Medical Compendium Journal:
Journal of the American Heart Association

Showing 21 to 30 of 64 articles

Predicting and Recognizing Drug-Induced Type I Brugada Pattern Using ECG-Based Deep Learning.

Journal of the American Heart Association
BACKGROUND: Brugada syndrome (BrS) has been associated with sudden cardiac death in otherwise healthy subjects, and drug-induced BrS accounts for 55% to 70% of all patients with BrS. This study aims to develop a deep convolutional neural network and ...

Predicting Outcomes Following Lower Extremity Endovascular Revascularization Using Machine Learning.

Journal of the American Heart Association
BACKGROUND: Lower extremity endovascular revascularization for peripheral artery disease carries nonnegligible perioperative risks; however, outcome prediction tools remain limited. Using machine learning, we developed automated algorithms that predi...

Monitoring of Remotely Reprogrammable Implantable Loop Recorders With Algorithms to Reduce False-Positive Alerts.

Journal of the American Heart Association
BACKGROUND: Implantable loop recorders (ILRs) are increasingly placed for arrhythmia detection. However, historically, ≈75% of ILR alerts are false positives, requiring significant time and effort for adjudication. The LINQII and LUX-Dx are remotely ...

Artificial Intelligence of Arterial Doppler Waveforms to Predict Major Adverse Outcomes Among Patients Evaluated for Peripheral Artery Disease.

Journal of the American Heart Association
BACKGROUND: Patients with peripheral artery disease are at increased risk for major adverse cardiac events, major adverse limb events, and all-cause death. Developing tools capable of identifying those patients with peripheral artery disease at great...

Deep Learning Algorithms to Detect Murmurs Associated With Structural Heart Disease.

Journal of the American Heart Association
Background The success of cardiac auscultation varies widely among medical professionals, which can lead to missed treatments for structural heart disease. Applying machine learning to cardiac auscultation could address this problem, but despite rece...

Validation of a Deep Learning Algorithm for Continuous, Real-Time Detection of Atrial Fibrillation Using a Wrist-Worn Device in an Ambulatory Environment.

Journal of the American Heart Association
BACKGROUND: Wearable devices may be useful for identification, quantification and characterization, and management of atrial fibrillation (AF). To date, consumer wrist-worn devices for AF detection using photoplethysmography-based algorithms perform ...

Supervised Text Classification System Detects Fontan Patients in Electronic Records With Higher Accuracy Than Codes.

Journal of the American Heart Association
Background The Fontan operation is associated with significant morbidity and premature mortality. Fontan cases cannot always be identified by () codes, making it challenging to create large Fontan patient cohorts. We sought to develop natural langua...

Survey and Evaluation of Hypertension Machine Learning Research.

Journal of the American Heart Association
Background Machine learning (ML) is pervasive in all fields of research, from automating tasks to complex decision-making. However, applications in different specialities are variable and generally limited. Like other conditions, the number of studie...

Identifying Reasons for Statin Nonuse in Patients With Diabetes Using Deep Learning of Electronic Health Records.

Journal of the American Heart Association
Background Statins are guideline-recommended medications that reduce cardiovascular events in patients with diabetes. Yet, statin use is concerningly low in this high-risk population. Identifying reasons for statin nonuse, which are typically describ...