AI Medical Compendium Journal:
Cardiovascular digital health journal

Showing 1 to 9 of 9 articles

Reducing the burden of inconclusive smart device single-lead ECG tracings via a novel artificial intelligence algorithm.

Cardiovascular digital health journal
BACKGROUND: Multiple smart devices capable of automatically detecting atrial fibrillation (AF) based on single-lead electrocardiograms (SL-ECG) are presently available. The rate of inconclusive tracings by manufacturers' algorithms is currently too h...

A machine learning-based clinical decision support algorithm for reducing unnecessary coronary angiograms.

Cardiovascular digital health journal
BACKGROUND: Conventional clinical risk scores and diagnostic algorithms are proving to be suboptimal in the prediction of obstructive coronary artery disease, contributing to the low diagnostic yield of invasive angiography. Machine learning could he...

Anatomically informed deep learning on contrast-enhanced cardiac magnetic resonance imaging for scar segmentation and clinical feature extraction.

Cardiovascular digital health journal
BACKGROUND: Visualizing fibrosis on cardiac magnetic resonance (CMR) imaging with contrast enhancement (late gadolinium enhancement; LGE) is paramount in characterizing disease progression and identifying arrhythmia substrates. Segmentation and fibro...

Diagnostic utility of artificial intelligence for left ventricular scar identification using cardiac magnetic resonance imaging-A systematic review.

Cardiovascular digital health journal
BACKGROUND: Accurate, rapid quantification of ventricular scar using cardiac magnetic resonance imaging (CMR) carries importance in arrhythmia management and patient prognosis. Artificial intelligence (AI) has been applied to other radiological chall...

Rationale and design of the SafeHeart study: Development and testing of a mHealth tool for the prediction of arrhythmic events and implantable cardioverter-defibrillator therapy.

Cardiovascular digital health journal
BACKGROUND: Patients with an implantable cardioverter-defibrillator (ICD) are at a high risk of malignant ventricular arrhythmias. The use of remote ICD monitoring, wearable devices, and patient-reported outcomes generate large volumes of potential v...

An artificial intelligence-enabled ECG algorithm for comprehensive ECG interpretation: Can it pass the 'Turing test'?

Cardiovascular digital health journal
OBJECTIVE: To develop an artificial intelligence (AI)-enabled electrocardiogram (ECG) algorithm capable of comprehensive, human-like ECG interpretation and compare its diagnostic performance against conventional ECG interpretation methods.

Large-scale identification of aortic stenosis and its severity using natural language processing on electronic health records.

Cardiovascular digital health journal
BACKGROUND: Systematic case identification is critical to improving population health, but widely used diagnosis code-based approaches for conditions like valvular heart disease are inaccurate and lack specificity.

Deep learning to estimate cardiac magnetic resonance-derived left ventricular mass.

Cardiovascular digital health journal
BACKGROUND: Cardiac magnetic resonance (CMR) is the gold standard for left ventricular hypertrophy (LVH) diagnosis. CMR-derived LV mass can be estimated using proprietary algorithms (eg, InlineVF), but their accuracy and availability may be limited.