AIMC Topic: Stroke Volume

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Electrocardiograph analysis for risk assessment of heart failure with preserved ejection fraction: A deep learning model.

ESC heart failure Oct 27, 2024
AIMS: Heart failure with preserved ejection fraction (HFpEF) requires an efficient screening method. We developed a deep learning model (DLM) to screen HFpEF risk using electrocardiograms (ECGs).
Humans Prospective Studies Middle Aged Risk Assessment Deep Learning Electrocardiography Heart Failure Female Aged Male Ventricular Function, Left Stroke Volume
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Automated Identification of Heart Failure With Reduced Ejection Fraction Using Deep Learning-Based Natural Language Processing.

JACC. Heart failure Oct 23, 2024
BACKGROUND: The lack of automated tools for measuring care quality limits the implementation of a national program to assess guideline-directed care in heart failure with reduced ejection fraction (HFrEF).
Natural Language Processing Patient Discharge Stroke Volume Humans Heart Failure Female Echocardiography Aged Middle Aged Aged, 80 and over Deep Learning Male
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Deep Learning-based 12-Lead Electrocardiogram for Low Left Ventricular Ejection Fraction Detection in Patients.

The Canadian journal of cardiology Sep 27, 2024
BACKGROUND: Reduced left ventricular ejection fraction (LVEF) initiates heart failure, and promptly identifying low ejection fraction is crucial for managing progression and averting mortality. In this study we developed an artificial intelligence-en...
Electrocardiography Follow-Up Studies Heart Failure Humans Ventricular Dysfunction, Left Algorithms Female Male Aged Ventricular Function, Left Stroke Volume Middle Aged Deep Learning
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Predicting stroke volume variation using central venous pressure waveform: a deep learning approach.

Physiological measurement Sep 17, 2024
. This study evaluated the predictive performance of a deep learning approach to predict stroke volume variation (SVV) from central venous pressure (CVP) waveforms.. Long short-term memory (LSTM) and the feed-forward neural network were sequenced to ...
Stroke Volume Middle Aged Deep Learning Signal Processing, Computer-Assisted Humans Central Venous Pressure Female Aged Adult Male
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Rule-based natural language processing to examine variation in worsening heart failure hospitalizations by age, sex, race and ethnicity, and left ventricular ejection fraction.

American heart journal Sep 7, 2024
BACKGROUND: Prior studies characterizing worsening heart failure events (WHFE) have been limited in using structured healthcare data from hospitalizations, and with little exploration of sociodemographic variation. The current study examined the impa...
Sex Factors California Racial Groups Adult Male Ventricular Function, Left Stroke Volume Middle Aged Disease Progression Age Factors Natural Language Processing Heart Failure Ethnicity Humans Female Hospitalization Aged Aged, 80 and over
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Artificial Intelligence-Enhanced Risk Stratification of Cancer Therapeutics-Related Cardiac Dysfunction Using Electrocardiographic Images.

Circulation. Cardiovascular quality and outcomes Sep 2, 2024
BACKGROUND: Risk stratification strategies for cancer therapeutics-related cardiac dysfunction (CTRCD) rely on serial monitoring by specialized imaging, limiting their scalability. We aimed to examine an application of artificial intelligence (AI) to...
Artificial Intelligence Retrospective Studies Female Risk Factors Aged Humans Antineoplastic Agents Time Factors United States Electrocardiography Predictive Value of Tests Male Ventricular Function, Left Stroke Volume Middle Aged Risk Assessment Ventricular Dysfunction, Left Trastuzumab Cardiotoxicity Anthracyclines
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Automated echocardiographic diastolic function grading: A hybrid multi-task deep learning and machine learning approach.

International journal of cardiology Aug 30, 2024
BACKGROUND: Assessing left ventricular diastolic function (LVDF) with echocardiography as per ASE guidelines is tedious and time-consuming. The study aims to develop a fully automatic approach of this procedure by a lightweight hybrid algorithm combi...
Stroke Volume Echocardiography Algorithms Middle Aged Humans Female Deep Learning Machine Learning Aged Diastole Male Ventricular Function, Left
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Prediction of 90 day readmission in heart failure with preserved ejection fraction by interpretable machine learning.

ESC heart failure Aug 21, 2024
AIMS: Certain critical risk factors of heart failure with preserved ejection fraction (HFpEF) patients were significantly different from those of heart failure with reduced ejection fraction (HFrEF) patients, resulting in the limitations of existing ...
Humans Machine Learning Prognosis Retrospective Studies Female Patient Readmission Middle Aged Risk Factors Risk Assessment Aged Time Factors Male Follow-Up Studies Stroke Volume Heart Failure
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Clinical utility of a rapid two-dimensional balanced steady-state free precession sequence with deep learning reconstruction.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Jul 28, 2024
BACKGROUND: Cardiovascular magnetic resonance (CMR) cine imaging is still limited by long acquisition times. This study evaluated the clinical utility of an accelerated two-dimensional (2D) cine sequence with deep learning reconstruction (Sonic DL) t...
Middle Aged Heart Ventricles Aged Deep Learning Humans Image Interpretation, Computer-Assisted Time Factors Adult Prospective Studies Observer Variation Predictive Value of Tests Male Female Magnetic Resonance Imaging, Cine Ventricular Function, Left Reproducibility of Results Ventricular Function, Right Stroke Volume
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Artificial intelligence-derived left ventricular strain in echocardiography in patients treated with chemotherapy.

The international journal of cardiovascular imaging Jul 23, 2024
Global longitudinal strain (GLS) is an echocardiographic measure to detect chemotherapy-related cardiovascular dysfunction. However, its limited availability and the needed expertise may restrict its generalization. Artificial intelligence (AI)-based...
Observer Variation Cardiotoxicity Reproducibility of Results Aged Aged, 80 and over Male Predictive Value of Tests Ventricular Function, Left Stroke Volume Heart Ventricles Echocardiography Humans Ventricular Remodeling Middle Aged Artificial Intelligence Ventricular Dysfunction, Left Neoplasms Retrospective Studies Image Interpretation, Computer-Assisted Antineoplastic Agents Female
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