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From: Google Scholar Alerts [scholaralerts-noreply@google.com](mailto:scholaralerts-noreply@google.com)
Date: Sun, Mar 10, 2024 at 12:29 AM
Subject: J Weston Hughes - new related research
To: [amir9979@gmail.com](mailto:amir9979@gmail.com)
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[PDF] Genetic analysis of cardiac dynamic flow volumes identifies loci mapping aortic root size
PB Munroe, N Aung, J Ramírez - Nature Genetics, 2024
An open-source automated algorithm called DeepFlow enables large-scale
derivation of aortic flow measurements, and genetic analysis of aortic flow, structural
and functional traits demonstrates a causal relationship between aortic size and …
Development and Validation of an Electrocardiographic Artificial Intelligence Model for Detection of Peripartum Cardiomyopathy
I Karabayir, G Wilkie, T Celik, L Butler, L Chinthala… - American Journal of …, 2024
BACKGROUND This study used electrocardiogram (ECG) data in conjunction with
artificial intelligence (AI) methods as a non-invasive tool for detecting peripartum
cardiomyopathy (PPCM). OBJECTIVE The primary objective was to assess the …
[HTML] Automated Atrial Fibrillation Diagnosis by Echocardiography without ECG: Accuracy and Applications of a New Deep Learning Approach
N Lu, H Vaseli, M Mahdavi, F Taheri Dezaki, C Luong… - Diseases, 2024
Background: Automated rhythm detection on echocardiography through artificial
intelligence (AI) has yet to be fully realized. We propose an AI model trained to
identify atrial fibrillation (AF) using apical 4-chamber (AP4) cines without requiring …
[HTML] Incidental Arrhythmias During Atrial Fibrillation Screening With Repeat 7‐Day Holter ECGs in a Hospital‐Based Patient Population
E Goulouti, A Lam, N Nozica, E Elchinova, C Dernektsi… - Journal of the American …, 2024
Background Screening for atrial fibrillation (AF) may reveal incidental arrhythmias of
relevance. The aim of this study was to describe incidental arrhythmias detected
during screening for AF in the STAR‐FIB (Predicting SilenT AtRial FIBrillation in …
[PDF] Attention-assisted hybrid CNN-BILSTM-BiGRU model with SMOTE–Tomek method to detect cardiac arrhythmia based on 12-lead electrocardiogram signals
S Chopannejad, A Roshanpoor, F Sadoughi - DIGITAL HEALTH, 2024
Objectives Cardiac arrhythmia is one of the most severe cardiovascular diseases that
can be fatal. Therefore, its early detection is critical. However, detecting types of
arrhythmia by physicians based on visual identification is time-consuming and …
[HTML] The feasibility of population screening for paroxysmal atrial fibrillation using handheld ECGs
J Mant, RN Modi, P Charlton, A Dymond, E Massou… - Europace, 2024
Abstract Background and Aims There are few data on the feasibility of population
screening for paroxysmal AF using hand-held ECG devices outside a specialist
setting or in people over the age of 75. We investigated the feasibility of screening …
Electrocardiographic patterns and clinical outcomes of acute coronary syndrome cardiogenic shock in patients undergoing percutaneous coronary intervention—A …
N D'Elia, S Vogrin, AL Brennan, D Dinh, J Lefkovits… - Cardiovascular …, 2024
Objectives To determine the influence of presenting electrocardiographic (ECG)
changes on prognosis in acute coronary syndrome cardiogenic shock (ACS-CS)
patients undergoing percutaneous coronary angiography (PCI). Background The …
[HTML] Dissecting the latent representation of age inside a deep neural network's predictions of diastolic dysfunction using echocardiographic variables
AD Jamthikar, R Shah, M Tokodi, PP Sengupta… - … Signal Processing and …, 2024
Objective This study explored the hidden layer activations of previously published
Deep Neural Networks (DNNs) that detect age-related diastolic function changes
through echocardiographic parameters. The study also aimed to decode the …
Evaluation of an algorithm‐guided photoplethysmography for atrial fibrillation burden using a smartwatch
Z Zhao, Q Li, S Li, Q Guo, X Bo, X Kong, S Xia, X Li… - Pacing and Clinical …, 2024
Background Wearable devices based on the PPG algorithm can detect atrial
fibrillation (AF) effectively. However, further investigation of its application on long‐
term, continuous monitoring of AF burden is warranted. Method The performance of a …
[HTML] Beyond Atrial Fibrillation: Machine Learning Algorithm Predicts Stroke in Adult Patients With Congenital Heart Disease
A Chiriac, C Ngufor, HK van Houten, R Mwangi… - Mayo Clinic Proceedings …, 2024
Objective To develop and validate a robust risk prediction model for stroke and
systemic embolism (SSE) in adult patients with congenital heart disease (ACHD),
using artificial intelligence. Patients and Methods Deidentified insurance claims from …
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