AIMC Topic: Models, Cardiovascular

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Blood Pressure Model Based on Hybrid Feature Convolution Neural Network in Promoting Rehabilitation of Patients with Hypertensive Intracerebral Hemorrhage.

Computational and mathematical methods in medicine Dec 7, 2021
OBJECTIVE: Accurate prediction of the rise of blood pressure is essential for the hypertensive intracerebral hemorrhage. This study uses the hybrid feature convolution neural network to establish the blood pressure model instead of the traditional me...
Male Algorithms Intracranial Hemorrhage, Hypertensive Middle Aged Female Antihypertensive Agents Computational Biology Aged Pulse Wave Analysis Blood Pressure Adult Humans Recurrence Models, Cardiovascular Neural Networks, Computer Machine Learning
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Artificial intelligence model comparison for risk factor analysis of patent ductus arteriosus in nationwide very low birth weight infants cohort.

Scientific reports Nov 16, 2021
Despite the many comorbidities and high mortality rate in preterm infants with patent ductus arteriosus (PDA), therapeutic strategies vary depending on the clinical setting, and most studies of the related risk factors are based on small sample popul...
Risk Factors Male Cohort Studies Registries Infant, Premature Models, Cardiovascular Ductus Arteriosus, Patent Infant, Very Low Birth Weight Humans Artificial Intelligence Female Infant, Newborn
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A deep learning approach to identify and segment alpha-smooth muscle actin stress fiber positive cells.

Scientific reports Nov 8, 2021
Cardiac fibrosis is a pathological process characterized by excessive tissue deposition, matrix remodeling, and tissue stiffening, which eventually leads to organ failure. On a cellular level, the development of fibrosis is associated with the activa...
Image Processing, Computer-Assisted Fibroblasts Myofibroblasts Myocardium Humans Artificial Intelligence Cells, Cultured Deep Learning Cell Culture Techniques Cardiomyopathies Models, Cardiovascular Hydrogels Stress Fibers Actins Surface Properties Elasticity
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A method of parameter estimation for cardiovascular hemodynamics based on deep learning and its application to personalize a reduced-order model.

International journal for numerical methods in biomedical engineering Oct 11, 2021
Precise model personalization is a key step towards the application of cardiovascular physical models. In this manuscript, we propose to use deep learning (DL) to solve the parameter estimation problem in cardiovascular hemodynamics. Based on the con...
Humans Neural Networks, Computer Algorithms Hemodynamics Deep Learning Models, Cardiovascular
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Machine Learning Models for Survival and Neurological Outcome Prediction of Out-of-Hospital Cardiac Arrest Patients.

BioMed research international Sep 17, 2021
BACKGROUND: Out-of-hospital cardiac arrest (OHCA) is a major health problem worldwide, and neurologic injury remains the leading cause of morbidity and mortality among survivors of OHCA. The purpose of this study was to investigate whether a machine ...
Brain Female Aged Sensitivity and Specificity Survival Analysis Humans Male Models, Cardiovascular Machine Learning ROC Curve Out-of-Hospital Cardiac Arrest Algorithms Predictive Value of Tests Area Under Curve
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Geometric and biomechanical modeling aided by machine learning improves the prediction of growth and rupture of small abdominal aortic aneurysms.

Scientific reports Sep 10, 2021
It remains difficult to predict when which patients with abdominal aortic aneurysm (AAA) will require surgery. The aim was to study the accuracy of geometric and biomechanical analysis of small AAAs to predict reaching the threshold for surgery, diam...
Clinical Decision-Making Biomechanical Phenomena ROC Curve Aortic Aneurysm, Abdominal Machine Learning Algorithms Prognosis Tomography, X-Ray Computed Models, Cardiovascular Aortic Rupture Area Under Curve Disease Management Aorta, Abdominal Computed Tomography Angiography Humans
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Explainable machine-learning predictions for complications after pediatric congenital heart surgery.

Scientific reports Aug 26, 2021
The quality of treatment and prognosis after pediatric congenital heart surgery remains unsatisfactory. A reliable prediction model for postoperative complications of congenital heart surgery patients is essential to enable prompt initiation of thera...
Infant Child, Preschool ROC Curve Cardiac Surgical Procedures Outcome Assessment, Health Care Prognosis Heart Defects, Congenital Female Models, Cardiovascular Male Postoperative Complications Humans Machine Learning Algorithms
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A clinical deep learning framework for continually learning from cardiac signals across diseases, time, modalities, and institutions.

Nature communications Jul 9, 2021
Deep learning algorithms trained on instances that violate the assumption of being independent and identically distributed (i.i.d.) are known to experience destructive interference, a phenomenon characterized by a degradation in performance. Such a v...
Models, Cardiovascular Deep Learning Time Factors ROC Curve Decision Support Systems, Clinical Electrocardiography Seasons Humans Arrhythmias, Cardiac Clinical Decision-Making Datasets as Topic
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Combined deep CNN-LSTM network-based multitasking learning architecture for noninvasive continuous blood pressure estimation using difference in ECG-PPG features.

Scientific reports Jun 29, 2021
The pulse arrival time (PAT), the difference between the R-peak time of electrocardiogram (ECG) signal and the systolic peak of photoplethysmography (PPG) signal, is an indicator that enables noninvasive and continuous blood pressure estimation. Howe...
Humans Machine Learning Blood Pressure Databases, Factual Heart Rate Models, Cardiovascular Photoplethysmography Blood Pressure Determination
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A new deep learning algorithm of 12-lead electrocardiogram for identifying atrial fibrillation during sinus rhythm.

Scientific reports Jun 17, 2021
Atrial fibrillation (AF) is the most prevalent arrhythmia and is associated with increased morbidity and mortality. Its early detection is challenging because of the low detection yield of conventional methods. We aimed to develop a deep learning-bas...
Neural Networks, Computer Artificial Intelligence Models, Cardiovascular ROC Curve Sinoatrial Node Algorithms Aged Humans Electrocardiography Female Male Atrial Fibrillation Middle Aged Probability Deep Learning
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