AIMC Topic: Systole

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Pattern recognition and prognostic analysis of longitudinal blood pressure records in hemodialysis treatment based on a convolutional neural network.

Journal of biomedical informatics Aug 24, 2019
OBJECTIVE: The aim of this study is to analyze and visualize blood pressure (BP) patterns during continuous hemodialysis (HD) sessions, referred to as multiple-session patterns (MSPs), and explore whether deep learning models with MSPs have better pe...
Renal Dialysis Adolescent Blood Pressure Determination Blood Pressure Kidney Failure, Chronic Young Adult Adult Male Electronic Health Records Middle Aged Humans Female Deep Learning Reproducibility of Results Neural Networks, Computer Aged Prognosis Aged, 80 and over Nonlinear Dynamics Medical Informatics Pattern Recognition, Automated Systole
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Using machine learning to characterize heart failure across the scales.

Biomechanics and modeling in mechanobiology Jun 25, 2019
Heart failure is a progressive chronic condition in which the heart undergoes detrimental changes in structure and function across multiple scales in time and space. Multiscale models of cardiac growth can provide a patient-specific window into the p...
Machine Learning Computer Simulation Female Models, Cardiovascular Muscle Cells Heart Ventricles Heart Failure Elasticity Systole Diastole Animals Male Swine Time Factors Myocardium
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Statistical Approaches Based on Deep Learning Regression for Verification of Normality of Blood Pressure Estimates.

Sensors (Basel, Switzerland) May 8, 2019
Oscillometric blood pressure (BP) monitors currently estimate a single point but do not identify variations in response to physiological characteristics. In this paper, to analyze BP's normality based on oscillometric measurements, we use statistical...
Young Adult Adult Male Middle Aged Deep Learning Algorithms Female Reproducibility of Results Aged Aged, 80 and over Statistics as Topic Diastole Adolescent Child Regression Analysis Blood Pressure Systole Humans
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The Role of GDF-15 in Heart Failure Patients With Chronic Kidney Disease.

The Canadian journal of cardiology Dec 26, 2018
BACKGROUND: Growth differentiation factor-15 (GDF-15) is a stress-inducible cytokine and member of the transforming growth factor-β cytokine superfamily that refines prognostic assessment in subgroups of patients with heart failure (HF). We evaluated...
Proportional Hazards Models Cholesterol Angiotensin Receptor Antagonists Humans Systole Sodium Middle Aged Biomarkers Angiotensin-Converting Enzyme Inhibitors Sex Factors Renal Insufficiency, Chronic Female Growth Differentiation Factor 15 Glomerular Filtration Rate Heart-Assist Devices Male Heart Failure, Systolic Follow-Up Studies Natriuretic Peptide, Brain Heart Transplantation Blood Pressure
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Machine learning based framework to predict cardiac arrests in a paediatric intensive care unit : Prediction of cardiac arrests.

Journal of clinical monitoring and computing Sep 27, 2018
A cardiac arrest is a life-threatening event, often fatal. Whilst clinicians classify some of the cardiac arrests as potentially predictable, the majority are difficult to identify even in a post-incident analysis. Changes in some patients' physiolog...
Monitoring, Physiologic Blood Pressure Oxygen Signal Processing, Computer-Assisted Heart Rate Critical Care Systole Respiratory Rate Heart Arrest Sensitivity and Specificity Infant Humans Software Child, Preschool Machine Learning Critical Illness Child Intensive Care Units, Pediatric Infant, Newborn Reproducibility of Results
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Heart Sound Segmentation-An Event Detection Approach Using Deep Recurrent Neural Networks.

IEEE transactions on bio-medical engineering Jun 1, 2018
OBJECTIVE: In this paper, we accurately detect the state-sequence first heart sound (S1)-systole-second heart sound (S2)-diastole, i.e., the positions of S1 and S2, in heart sound recordings. We propose an event detection approach without explicitly ...
Neural Networks, Computer Algorithms Signal Processing, Computer-Assisted Sound Spectrography Diastole Systole Humans Heart Sounds Phonocardiography
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A Novel Neural Network Model for Blood Pressure Estimation Using Photoplethesmography without Electrocardiogram.

Journal of healthcare engineering Mar 7, 2018
The prevention, evaluation, and treatment of hypertension have attracted increasing attention in recent years. As photoplethysmography (PPG) technology has been widely applied to wearable sensors, the noninvasive estimation of blood pressure (BP) usi...
Databases, Factual Female Reproducibility of Results Aged Aged, 80 and over Young Adult Adult Male Middle Aged Hypertension Humans Neural Networks, Computer Critical Care Photoplethysmography Pattern Recognition, Automated Electrocardiography Systole Blood Pressure Determination Diastole Blood Pressure Pulse Wave Analysis
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Impact of coronary artery disease on augmentation index as measured by estimated central blood pressure: A case control study in Asian Indians.

Indian heart journal Dec 6, 2017
AIMS: We compared various components of blood pressure and arterial stiffness of healthy control with those of coronary artery disease (CAD) patients using BP+ machine™.
Radial Artery Aged Aged, 80 and over Adult Vascular Stiffness Male Humans Case-Control Studies Coronary Artery Disease Prospective Studies Middle Aged Incidence Asian People Female India Arterial Pressure Blood Pressure Determination Systole Follow-Up Studies
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Convolutional Neural Network for the Detection of End-Diastole and End-Systole Frames in Free-Breathing Cardiac Magnetic Resonance Imaging.

Computational and mathematical methods in medicine Jul 26, 2017
Free-breathing cardiac magnetic resonance (CMR) imaging has short examination time with high reproducibility. Detection of the end-diastole and the end-systole frames of the free-breathing cardiac magnetic resonance, supplemented by visual identifica...
Heart Systole Diastole Humans Neural Networks, Computer Reproducibility of Results Magnetic Resonance Imaging
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Deep Learning for identifying systolic complexes in SCG traces: a cross-dataset analysis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
The seismocardiographic signal is a promising alternative to the traditional ECG in the analysis of the cardiac activity. In particular, the systolic complex is known to be the most informative part of the seismocardiogram, thus requiring further ana...
Algorithms Deep Learning Electrocardiography Signal Processing, Computer-Assisted Systole Humans
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