相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。Reconstruction of central arterial pressure waveform based on CNN-BILSTM
Hanguang Xiao et al.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2022)
Transportation noise pollution and cardiovascular disease
Thomas Munzel et al.
NATURE REVIEWS CARDIOLOGY (2021)
Blood Pressure Morphology Assessment from Photoplethysmogram and Demographic Information Using Deep Learning with Attention Mechanism
Nicolas Aguirre et al.
SENSORS (2021)
A novel electrical impedance function to estimate central aortic blood pressure waveforms
Denesh Sooriamoorthy et al.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2021)
Aortic blood pressure estimation: A hybrid machine-learning and cross-relation approach
Ahmed Magbool et al.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2021)
A review on the attention mechanism of deep learning
Zhaoyang Niu et al.
NEUROCOMPUTING (2021)
Imputation of the continuous arterial line blood pressure waveform from non-invasive measurements using deep learning
Brian L. Hill et al.
SCIENTIFIC REPORTS (2021)
Automated Noninvasive Central Blood Pressure Measurements by Oscillometric Radial Pulse Wave Analysis: Results of the MEASURE-cBP Validation Studies
Frederik Trinkmann et al.
AMERICAN JOURNAL OF HYPERTENSION (2021)
Machine learning in cardiovascular flows modeling: Predicting arterial blood pressure from non-invasive 4D flow MRI data using physics-informed neural networks
Georgios Kissas et al.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2020)
European Society of Cardiology: Cardiovascular Disease Statistics 2019
Adam Timmis et al.
EUROPEAN HEART JOURNAL (2020)
Central blood pressure for the management of hypertension: Is it a practical clinical tool in current practice?
Hao-Min Cheng et al.
JOURNAL OF CLINICAL HYPERTENSION (2020)
Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) network
Alex Sherstinsky
PHYSICA D-NONLINEAR PHENOMENA (2020)
A review of machine learning techniques in photoplethysmography for the non-invasive cuff-less measurement of blood pressure
C. El-Hajj et al.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2020)
End-To-End Deep Learning Architecture for Continuous Blood Pressure Estimation Using Attention Mechanism
Heesang Eom et al.
SENSORS (2020)
Continuous blood pressure measurement from one-channel electrocardiogram signal using deep-learning techniques
Fen Miao et al.
ARTIFICIAL INTELLIGENCE IN MEDICINE (2020)
Generalized Deep Neural Network Model for Cuffless Blood Pressure Estimation with Photoplethysmogram Signal Only
Yan-Cheng Hsu et al.
SENSORS (2020)
Real-Time Cuffless Continuous Blood Pressure Estimation Using Deep Learning Model
Yung-Hui Li et al.
SENSORS (2020)
Long short-term memory - Fully connected (LSTM-FC) neural network for PM2.5 concentration prediction
Jiachen Zhao et al.
CHEMOSPHERE (2019)
A Non-Invasive Continuous Blood Pressure Estimation Approach Based on Machine Learning
Shuo Chen et al.
SENSORS (2019)
Pulse transit time estimation of aortic pulse wave velocity and blood pressure using machine learning and simulated training data
Janne M. J. Huttunen et al.
PLOS COMPUTATIONAL BIOLOGY (2019)
Multiscale mathematical modeling vs. the generalized transfer function approach for aortic pressure estimation: a comparison with invasive data
Andrea Guala et al.
HYPERTENSION RESEARCH (2019)
A call for deep-learning healthcare
Beau Norgeot et al.
NATURE MEDICINE (2019)
Recommendations and Practical Guidance for performing and reporting validation studies according to the Universal Standard for the validation of blood pressure measuring devices by the Association for the Advancement of Medical Instrumentation/European Society of Hypertension/International Organization for Standardization (AAMI/ESH/ISO)
George S. Stergiou et al.
JOURNAL OF HYPERTENSION (2019)
N-Point Moving Average: A Special Generalized Transfer Function Method for Estimation of Central Aortic Blood Pressure
Hanguang Xiao et al.
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING (2018)
Arrhythmia detection using deep convolutional neural network with long duration ECG signals
Ozal Yildirim et al.
COMPUTERS IN BIOLOGY AND MEDICINE (2018)
Obstructive sleep apnoea detection using convolutional neural network based deep learning framework
Debangshu Dey et al.
BIOMEDICAL ENGINEERING LETTERS (2018)
Model-based cardiovascular disease diagnosis: a preliminary in-silico study
Shiva Ebrahimi Nejad et al.
BIOMECHANICS AND MODELING IN MECHANOBIOLOGY (2017)
Blood Pressure Estimation Using Pulse Transit Time From Bioimpedance and Continuous Wave Radar
Dilpreet Buxi et al.
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING (2017)
Estimation of aortic systolic blood pressure from radial systolic and diastolic blood pressures alone using artificial neural networks
Hanguang Xiao et al.
JOURNAL OF HYPERTENSION (2017)
Attentional control and the self: The Self-Attention Network (SAN)
Glyn W. Humphreys et al.
COGNITIVE NEUROSCIENCE (2016)
Obesity and Cardiovascular Disease
Francisco B. Ortega et al.
CIRCULATION RESEARCH (2016)
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
Hoo-Chang Shin et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING (2016)
A personalized-model-based central aortic pressure estimation method
Sheng Jiang et al.
JOURNAL OF BIOMECHANICS (2016)
Anxiety and Cardiovascular Disease Risk: a Review
Phillip J. Tully et al.
CURRENT CARDIOLOGY REPORTS (2016)
Central blood pressure: current evidence and clinical importance
Carmel M. McEniery et al.
EUROPEAN HEART JOURNAL (2014)
Cardiovascular disease prevention
G. Van Camp
ACTA CLINICA BELGICA (2014)
Noninvasive Studies of Central Aortic Pressure
Michael F. O'Rourke et al.
CURRENT HYPERTENSION REPORTS (2012)
Subject-Specific Estimation of Central Aortic Blood Pressure Using an Individualized Transfer Function: A Preliminary Feasibility Study
Jin-Oh Hahn et al.
IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE (2012)
Deep Learning and Its Applications to Signal and Information Processing
Dong Yu et al.
IEEE SIGNAL PROCESSING MAGAZINE (2011)
Development and Validation of a Novel Method to Derive Central Aortic Systolic Pressure From the Radial Pressure Waveform Using an N-Point Moving Average Method
Bryan Williams et al.
JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY (2011)
Role of Pulse Pressure Amplification in Arterial Hypertension Experts' Opinion and Review of the Data
Alberto P. Avolio et al.
HYPERTENSION (2009)
Noninvasive determination of carotid-femoral pulse wave velocity depends critically on assessment of travel distance: a comparison with invasive measurement
Thomas Weber et al.
JOURNAL OF HYPERTENSION (2009)
Arterial transfer functions and the reconstruction of central aortic waveforms: myths, controversies and misconceptions
Sarah A. Hope et al.
JOURNAL OF HYPERTENSION (2008)
Central pressure more strongly relates to vascular disease and outcome than does brachial pressure - The strong heart study
Mary J. Roman et al.
HYPERTENSION (2007)
Noninvasive (input) impedance, pulse wave velocity, and wave reflection in healthy middle-aged men and women
Patrick Segers et al.
HYPERTENSION (2007)
Blind system identification of noncoprime multichannel systems and its application to noninvasive cardiovascular monitoring
Y Zhang et al.
JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME (2004)
Prospective evaluation of a method for estimating ascending aortic pressure from the radial artery pressure waveform
AL Pauca et al.
HYPERTENSION (2001)
分享论文
