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Predicting Heart Failure. Группа авторов
Читать онлайн.Название Predicting Heart Failure
Год выпуска 0
isbn 9781119813033
Автор произведения Группа авторов
Жанр Медицина
Издательство John Wiley & Sons Limited
Chapter 4
AC | Alternative Current, 9 |
BSN | Body Sensor Network, 2 CE Counter Electrode, 5 |
CMT | Coupled-Mode Theory, 12 |
EDAS | European Aeronautic Defense and Space Company, 10 |
EM | Electromagnetic Interference, 11 |
EMF | Electromagnetic Field, 9 |
HPF | High-Pass Filter, 17 |
IoT | Internet of Things, 2 |
LPF | Low Pass Filter, 17 |
MEMS | Micro-Electromechanical Systems, 4 |
MPT | Microwave Power Transmission, 8 |
RE | Reference Electrode, 5 |
RF | Radio Frequency, 3 |
SHM | Structural Health Supervising, 2 |
SoC | System on a Chip, 5 |
VSWR | Voltage Standing Wave Ratio, 24 |
WBAN | Wireless Body Area Network, 2 |
WE | Working Electrode, 5 |
Chapter 5
BCG | Ballistocardiography, 13 |
BLUE | Bedside Lung Ultrasound, 10 |
BNP | B-type Natriuretic Peptide, 14 |
C.A.USE | Cardiac Arrest Ultrasound Exam, 10 |
CHF | Chronic Heart Failure, 2 |
DNN | Deep Neural Network, 12 |
ECG | Electrocardiography, 3 |
EVLW | Extravascular Lung Water, 8 |
FALLS | Fluid Administration Limited by Lung Sonography, 10 |
GPS | Global Positioning System, 6 |
HF | Heart failure, 2 |
ICD | Implantable Cardioverter Defibrillator, 12 |
LuCUS | Lung and Cardiac Ultrasound, 10 |
LUS | Lung Ultrasound, 8 |
LV | Left Ventricular, 7 |
MEMS | Microelectromechanical System, 6 |
MFCCs | Mel-frequency Cepstral Coefficients, 12 |
NT-proBNP | Amino-terminal Pro-B-type Natriuretic Peptide, 14 |
PA | Pulmonary Arterial, 7 |
PCG | Phonocardiogram, 12 |
PPG | Photoplethysmogram, 14 |
RCTs | Randomized Control Trials, 15 |
ReDS | Remote Dielectric Sensing Technology, 5 |
RPM | Remote Patient Monitoring, 15 |
RV | Right Ventricular, 7 |
SCG | Seismocardiography, 12 |
Chapter 6
ACM | All-cause Mortality, 8 |
AI | Artificial Intelligence, 3, 8 |
ANN | Artificial Neural Networks, 3,12 |
AUC | Area Under the Curve, 9 |
CAD | Coronary Artery Disease, 8 |
CCTA | Cardiac Computed Tomographic Angiography, 8 |
CMR | Cardiac Magnetic Resonance, 12 |
CNN | Convolutional Neural Networks, 12 |
DL | Deep learning, 12 |
ECG | Electrocardiogram, 9 |
FDA | Food and Drug Administration, 17 |
FFR | Fractional Flow Reserve, 9 |
FRS | Framingham Risk Score, 8 |
GAN | Generative Adversarial Networks, 11 |
GAN | Generative Adversarial Networks, 3 |
HFpEF | Heart Failure with Preserved Ejection Fraction, 10 |
HMM | Hidden Markov Model, 15 |
LASSO | Least Absolute Shrinkage and Selection Operator, 3 |
LV | Left Ventricle, 9 |
LVEF | Left Ventricular Ejection Fraction, 12 |
MDI | Modified Duke Index, 8 |
MFR | Myocardial Flow Reserve, 9 |
ML | Machine Learning, 3 |
MPI | Myocardial Perfusion Imaging, 15 |
MPS | Myocardial Perfusion Scan, 9 |
NER | Names Entity Recognition, 15 |
NLP | Natural Language Processing, 15 |
POS | Part of Speech, 15 |
PSA | Parsing or Syntactic Analysis, 15 |
RNN | Recurrent Neural Networks, 12 |
SIS | Segment Involvement Score, 8 |
SSS | Segment Stenosis Score, 8 |
STE | Speckle-tracking Echocardiography, 11 |
SVMs | Support Vector Machines, 8 |
TPD | Total Perfusion Deficit, 15 |
TTE | Transthoracic Echocardiogram, 12 |
Chapter 7
DT | Decision Tree, 2 |
K-NN | K-Nearest Neighbor, 5 |
LDA | Linear Discriminant Analysis, 2 |
MAFIA | Maximal Frequent Itemset Algorithm, 4 |
NB | Naïve Bayes, 2 |
NN | Neural Networks, 4 |
RF | Random Forest, 2 |
SVM | Support Vector Machine, 2 |
Chapter 8
AUPRC | Area Under Precision Recall curve, 10 |
AUROC | Area Under ROC Curve, 10 |
BNP | Brain Natriuretic Peptide, 4 |
CNN | Convolutional Neural Networks, 7 |
DAE | Denoising Autoencoder, 7 |
DBNs | Deep Belief Networks, 7 |
DT | Decision Tree, 7 |
ECG | Electrocardiogram, 3 |
EHR | Electronic Health Records, 5 |
EMB | Endomyocardial Biopsy, 7 |
ESC | European Society of Cardiology, 4 |
GBM | Gradient-boosted Model, 11 |
GRU RNNs | Gated Recurrent Unit Recurrent Neural Networks, 9 |
GWTG-HF | Get With The Guidelines-Heart Failure, 11 |
HF | Heart Failure, 2 |
KNNs | K-nearest Neighbors, 7 |
LAD | Left Atrial Dimension, 10 |
LR | Logistic Regression, 11 |
LSTM | Long Short-Term Memory, 7 |
MAGGIC | Meta-Analysis Global Group in Chronic, 11 |
ML | Machine Learning, 2 |
ReLU | Rectified Linear Unit, 8 |
RETAIN | REverse Time AttentIoN Model, 9 |
RF | Random Forest, 8 |
RNN | recurrent Neural Networks, 7 |
ROI | Regions of Interests, 8 |
RPM | Remote Patient Monitoring, 5 |
SVM | Support Vector Machine, 7 |
TAN | Tree-augmented Naive Bayesian, 11 |
Chapter 9
AF | Atrial Fibrillation, 9 |
AFL | Atrial Flutter, 10 |
AUC | Area Under the Roc Curve, 8 |
BN | Bayes Network, 31 |
CART | Classification and Regression Trees, 15 |
CFS | Correlation-based Feature Selection, 31 |
CMR | Cardiac Magnetic Resonance, 6 |
CNN | Convolutional Neural Network, 9 |
CTCA | Computed Tomography Coronary Angiography, 6 |
DL | Deep Learning, 8 |
DNN | Deep Neural Network, 9 |
DUNs | Deep Unified Networks, 20 |
ECG | Electrocardiogram, 6 |
EF | Ejection Fraction, 5 |
EFFECT | Enhanced Feedback for Effective Cardiac Treatment, 10 |
EHR | Electronic Health Record, 8 |
ELM | Extreme Learning Machine, 10 |
ESC | European Society of Cardiology, 6 |
GDS | Generalized Discriminant Analysis, 16 |
GLM | Generalized Linear Model, 23 |
HF | Heart Failure, 1 |
HFmrEF | HF with Mid-range or Mildly Reduced EF, 5 |
HFpEF | Heart Failure with Preserved Ejection Fraction, 5 |
HFrEF | Heart Failure with Reduced Ejection Fraction, 5 |
HRV | Heart Rate Variability, 9 |
K-NN | K-nearest Neighbor, 8 |
LGE | Late Gadolinium Enhancement, 6 |
LMT | Logistic Model Trees, 31 |
LR | Logistic Regression, 8 |
LS-SVM | Least Square SVM, 9 |
LSTM | Long Short-term
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