Читать книгу Predicting Heart Failure - Группа авторов - Страница 10
Abbreviations
ОглавлениеChapter 1
| 3-D | Three-dimensional, 10 |
| BNP | Brain Natriuretic Peptide, 9 |
| CAD | Coronary Artery Disease, 2 |
| CHF | Congestive Heart Failure, 3 |
| CRP | C-reactive Protein, 8 |
| HF | Heart Failure, 3 |
| HRV | Heart Rate Variability, 24 |
| IoT | Internet of Things, 11 |
| LS-SVM | Least Squares SVM, 24 |
| LV | Left Ventricular, 23 |
| SVM | Support Vector Machine, 18 |
Chapter 2
| ACS | Acute Coronary Syndrome, 8 |
| AI | Artificial Intelligence, 18 bp Blood Pressure, 12 |
| CAC | Coronary Artery Calcium, 21 |
| CCA | Common Carotid Artery, 19 |
| CHF | Congestive Heart Failure, 20 |
| CNN | Convolutional Neural Network, 20 |
| CQ-NSGT | Constant-Q Non-Stationary Gabor Transform, 20 |
| CT | Computed Tomography, 19 |
| CVDs | Cardiovascular Diseases, 19 |
| DNN | Deep Neural Network, 20 |
| DOE | Dyspnea on Exertion, 10 |
| ECG | Electrocardiogram, 5 |
| ELM | Extreme Learning Machines, 20 |
| FCN | Fully Convolutional Network, 20 |
| GERD | Gastroesophageal Reflux Disease, 9 |
| HDL | High-density Lipoprotein, 12 |
| ICA | Internal Carotid Artery, 19 |
| IMT | Intima-Media Thickness, 19 |
| LDL | Low-density Lipoprotein, 12 |
| LI | Lumen-intima, 19 |
| LII | Lumen-Intima Interface, 20 |
| MA | Media Adventitia, 19 |
| MAI | Media-Adventitia Interface, 20 |
| MLP | Multilayer Perceptron, 21 |
| MPI | Myocardial Perfusion Imaging, 22 |
| NSR | Normal Sinus Rhythm, 20 |
| PND | Paroxysmal Nocturnal Dyspnea, 11 |
Chapter 3
| BNP | Brain Natriuretic Peptide, 5 |
| CRP | C-Reactive Protein, 3 |
| CSGMs | Comb Structured Gold Microelectrode Arrays, 28 |
| cTnI | Cardiac Troponin I, 5 |
| CV | Cyclic Voltammetry, 28 |
| CVDs | Cardiovascular Diseases, 1 |
| DPV | Differential Pulse Voltammetry, 28 |
| EIS | Electrochemical Impedance Spectroscopy, 28 |
| ELISA | Enzyme-Linked Immunosorbent Assay, 29 |
| ENPs | Enzyme Nanoparticles, 29 |
| GDF | Growth Differentiation Factor, 7 |
| GK | Glycerol Kinase, 29 |
| GO | Graphene Oxide, 28 |
| GPO | Glycerol-3- Phosphate Oxidase, 29 |
| HDL | High-density Lipoprotein, 8 |
| hour-FABP | Heart Fatty Acid-Binding Protein, 7 |
| IL-6 | Interleukin-6, 7 |
| LDL | Low-density Lipoprotein, 8 |
| LOD | Limit of Detection, 10 |
| LSPR | Localized Surface Plasmon Resonance, 12 |
| miRNAs | Micro RNAs, 6 |
| MPO | Myeloperoxidase, 6 |
| NPs | Nanoparticles, 29 |
| NSE | Neuron-specific Enolase, 6 |
| PCT | Procalcitonin, 5 |
| PEC | Photoelectrochemical, 28 |
| PG | Pencil Graphite, 29 |
| QDs | Quantum Dots, 28 |
| SEM | Scanning Electron Microscopy, 28 |
| SERS | Surface-Enhanced Raman Scattering, 12 |
| SPEs | Screen-Printed Electrodes, 28 |
| SPGEs | Screen-Printed Gold Electrodes, 28 |
| SPR | Surface Plasmon Resonance, 12 |
| SPRi | Surface Plasmon Resonance Imaging, 12 |
| sST2 | Soluble Suppressor of Tumorgenicity 2, 8 |
| TG | Triglycerides, 9 |
| TNF-α, | Tumor Necrosis Factor-alpha, 7 |
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 Memory, 9 |
| MAGGIC | Meta-analysis Global Group in Chronic, 24 |
| ML | Machine Learning, 7 |
| MLP | Multilayer Perceptron, 8 |
| NB | Naïve Bayes, 34 |
| NLP | Natural Language Processing, 16 |
| NN | Neural Network, 8 |
| NRD | Nationwide Readmissions Database, 21 |
| NYHA | New York Heart Association, 5 |
| RBF | Radial Basis Function, 18 |
| RDW | Red Blood Cell Distribution Width, 26 |
| RF | Random Forest, 9 |
| RNN | Recurrent Neural Network, 8 |
| ROT | Rotation Forest, 16 |
| RS | Rough Set, 8 |
| RSA | Random Search Algorithm, 10 |
| SAE | Sparse Auto-encoder, 9 |
| SGD | Stochastic Gradient Descent, 9 |
| SVM | Support Vector Machines, 8 |
Chapter 10
| AI | Artificial Intelligence, 1 bp Blood Pressure, 11 |
| CAD | Coronary Artery Disease, 15 |
| CT | Computed Tomography, 15 |
| CVDs | Cardiovascular Diseases, 1 |
| DL | Deep Learning, 12 |
| ECG | Electrocardiogram, 1 |
| EIS | Electrochemical Impedance Spectroscopy, 4 |
| IoT | The Internet of Things, 11 |
| MRI | Magnetic Resonance Imaging, 2,13 |
| RI | Refractive Index, 6 |
Chapter 11
| BMI | Body Mass Index, 9 |
| CHF | Chronic Heart Failures, 2 |
| CIHM | Chronicle Implantable Hemodynamic Monitor, 19 |
| CRT | Cardiac Resynchronization Therapy, 19 |
| HCG | Human Chorionic Gonadotropin, 21 |
| IASD | Inter Atrial Shunt Device, 22 |
| LA | Left Atrial, 17 |
| LAP | Left Atrial Pressure, 18 |
| MCT | Mobile Cardiac Telemetry, 6 |
| NYHA | New York Heart Association, 19 |
| PA | Pulmonary Artery, 17 |
| PAM | Patient Advisory Module, 20 |
| RV | Right Ventricle, 17 |
Chapter 12
| AI | Artificial Intelligence, 3 |
| ANN | Artificial Neural Networks, 4 |
| AUC | Area Under Curve, 6 |
| CNN | Convolutional Neural Network, 4 |
| CRT | Cardiac Resynchronization Therapy, 6 |
| DL | Deep Learning, 3 |
| DNN | Deep Neural Network, 5 |
| ECG | Electrocardiographic, 5 |
| HF | Heart Failure, 1 |
| k-NN | k-Nearest Neighbors, 5 |
| LVAD | Left Ventricular Assist Device, 7 |
| ML | Machine Learning, 3 |
| PPGs | Photoplethysmograms, 8 |
| RF | Random Forest, 4 |
| RNN | Recurrent Neural Network, 5 |
| RV | Right Ventricular, 2 |
| RVF | Right-ventricular Failure, 7 |
| RVFRS | Right Ventricular Failure Risk Score, 7 |
| SVM | Support Vector Machine, 4 |
Chapter 13
| ABP | Arterial Blood Pressure, 4 |
| AF | Atrial Fibrillation, 11 |
| CAD | Coronary Artery Diseases, 19 |
| CardioMEMS | Cardio-Microelectromechanical system, 3 |
| CRT | Cardiac Resynchronization Therapy, 18 |
| CRT-D | Cardiac Resynchronization Therapy Defibrillator, 4 |
| CVDs | Cardiovascular Diseases, 3 |
| ECG | Electrocardiogram, 2 |
| FDA | Food and Drug Administration, 13 |
| HF | Heart Failure, 1 |
| hour | Heart Rate, 13 |
| ICDs | Implantable Cardioverter-defibrillators, 5 |
| LAP | Left Atrial Pressure, 5 |
| LVAD | Left Ventricular Assist Device, 18 |
| MI | Myocardial Infarction, 14 |
| NSTEMI | Non-ST-elevation Myocardial Infarction, 18 |
| NYHA | New York Heart Association, 10 |
| OHRM | Optical Heart Rate Monitor, 9 |
| PAP | Pulmonary Artery Pressure, 3 |
| PD | Photodiode, 9 |
| PPG | Photoplethysmogram, 4 |
| RR | Respiration Rate, 13 |
| STEMI | ST-elevation Myocardial Infarction, 18 |
| SVM | Support Vector Machine, 18 |
| VF | Ventricular Fibrillation, 11 |