AIMC Topic: Hypertrophy, Left Ventricular
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Deep learning to detect left ventricular structural abnormalities in chest X-rays.
European heart journal
Jun 7, 2024
BACKGROUND AND AIMS: Early identification of cardiac structural abnormalities indicative of heart failure is crucial to improving patient outcomes. Chest X-rays (CXRs) are routinely conducted on a broad population of patients, presenting an opportuni...
High-Throughput Precision Phenotyping of Left Ventricular Hypertrophy With Cardiovascular Deep Learning.
JAMA cardiology
Apr 1, 2022
IMPORTANCE: Early detection and characterization of increased left ventricular (LV) wall thickness can markedly impact patient care but is limited by under-recognition of hypertrophy, measurement error and variability, and difficulty differentiating ...
Artificial intelligence capable of detecting left ventricular hypertrophy: pushing the limits of the electrocardiogram?
Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
Mar 1, 2020
Comparing the performance of artificial intelligence and conventional diagnosis criteria for detecting left ventricular hypertrophy using electrocardiography.
Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
Mar 1, 2020
AIMS: Although left ventricular hypertrophy (LVH) has a high incidence and clinical importance, the conventional diagnosis criteria for detecting LVH using electrocardiography (ECG) has not been satisfied. We aimed to develop an artificial intelligen...
Detection of Left Ventricular Hypertrophy Using Bayesian Additive Regression Trees: The MESA.
Journal of the American Heart Association
Mar 5, 2019
Background We developed a new left ventricular hypertrophy ( LVH ) criterion using a machine-learning technique called Bayesian Additive Regression Trees ( BART ). Methods and Results This analysis included 4714 participants from MESA (Multi-Ethnic S...
Bayes Theorem
Ventricular Remodeling
Hypertrophy, Left Ventricular
Diagnosis, Computer-Assisted
United States
Electrocardiography
Magnetic Resonance Imaging
Decision Trees
Predictive Value of Tests
Male
Ventricular Function, Left
Machine Learning
Middle Aged
Female
Reproducibility of Results
Aged
Humans
Aged, 80 and over
Risk factors for diastolic left ventricular myocardial dysfunction in patients with chronic kidney disease.
Terapevticheskii arkhiv
Sep 20, 2018
AIM: To examine the frequency and risk factors for the development of diastolic dysfunction (DD) of the left ventricle (LV) of the heart in patients with chronic kidney disease (CKD).
P569Diastolic dyssynchrony is associated with exercise intolerance in hypertensive patients with left ventricular hypertrophy.
European heart journal. Cardiovascular Imaging
Dec 1, 2016
BACKGROUND: Left ventricular hypertrophy (LVH) is associated with intra-ventricular dyssynchrony at systolic phase during exercise in hypertensive patients. However, dypsnea on exertion is much more correlated with diastolic phase. We investigated wh...
Deterioration of left ventricular systolic function in extended Pacing to Avoid Cardiac Enlargement (PACE) trial: the predictive value of early systolic dyssynchrony.
Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
Oct 1, 2015
AIMS: Biventricular (BiV) pacing was superior to right ventricular apical (RVA) pacing at extended follow-up in the Pacing to Avoid Cardiac Enlargement (PACE) trial. Early pacing-induced systolic dyssynchrony (DYS) might be related to mid-term result...
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