Page 264 - Artificial Intelligence for Computational Modeling of the Heart

238 Index

Models fibers, 5 Posterolateral scar, 184
atrial, 43 infarction, 48 Pressure
blood flow, 203 remodeling, 19 arterial, 26, 31, 89
computational, 14, 18, 39, 41, scar, 47 atrial, 26, 31, 93
118, 120, 138, 160, 163, sheets, 20 blood, 18, 27, 28, 191
171–173, 184, 185, 210 thickening, 19 curves, 89, 92
electrophysiology, 17, 24, 89 tissues, 6, 10 drop, 29, 31, 34, 190–192,
hemodynamics, 18 ventricular, 4 197–200, 202
learning, 115, 171 Myofibers, 27 fields, 26, 87
lumped, 22, 24, 32 gradient, 29, 30, 38, 71
parameters, 10, 12, 28, 39, 40, O
110, 118, 137, 140, 143, 145, Ordinary differential equation measurements, 89, 190
152, 153, 162–164, 173, 174, (ODE), 33 oscillating, 36
192, 204 recovery, 199
personalization, 12, 18, 24, 43, P TLED, 86
88, 119, 150, 170, 181 Partial least squares regression values, 70
personalization algorithms, (PLSR), 138, 148 ventricular, 28, 32, 71, 123
161 Passive myocardium, 19 Principal component analysis
personalization problem, 170 Pathologically dilated ventricles, (PCA), 139, 140
synthetic, 195 34 Probabilistic Boosting Tree
valves, 37, 38, 45, 84 Patient specific anatomical (PBT), 99
Monodomain models, 128 Projection pursuit regression
equation, 143, 144, 151, 152 Percutaneous Coronary (PPR), 142
equation solution, 152 Intervention (PCI), 113, 118 Prosthetic
model, 12, 16, 17, 54, 143, 153, Performance, diagnostic, 134 aortic valves, 38
163 Pericardium, 4, 5, 71 mitral valves, 38
problem, 51, 152, 165 bag, 71 valves, 38
Morphological features, 202 cavity, 72 Pulmonary
Motion constraint, 26 circulation, 177, 203, 205, 206
analysis, 114 Peripheral resistance, 27, 31, 33 circulation distal resistance,
cardiac, 22, 71, 78, 113 Personalization
ground truth, 159 framework, 204 205
heart, 40, 84 models, 12, 18, 24, 43, 88, 119, resistance, 204, 205
patterns, 116 150, 170, 181 valve, 4, 29, 46, 49, 89, 205
valves, 30, 38, 79 objectives, 177 vein, 26, 33, 93
ventricular, 71 probabilistic, 173 vein pressure, 33, 93
Multivariate adaptive regression problem, 169 Purkinje
splines (MARS), 164 procedure, 90, 171, 173 fibers, 8, 9, 57
Myocardial strategy, 181 network, 14, 62, 90, 174
electrical diffusivity, 163 success, 171 hindered, 91
fibers, 8, 21, 43 workflow, 92 system, 57, 60, 137, 185
tissue, 51, 57, 58, 174 Personalized electrophysiology,
Myocardium, 4–7, 12, 14, 17, 19, 92
22, 25–27, 43, 46, 48, 66, 75, Phenomenological features, 141, Q
117, 151, 180, 185 142 QRS
architecture, 48 Phenomenological models, 9, complex, 66, 163, 188, 189
atrial, 137 10, 24, 138, 143 duration, 66, 90, 91, 164–166,
biomechanics, 18, 67 Physiological heart models, 97 168, 174, 180, 186–188, 190
conductivity, 91 Physiological models, 117, 169 shortening, 187–190