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Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_5234_Библиотеки_им_академика_М_И_Перельмана
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334 Index
Dopamine, 7, 8, 11, 91, 193, 194, 269, 272, 311
Dopaminergic, 7, 90, 241
Drug, 11, 12, 13, 22, 23, 25, 26, 29, 93, 94, 95,
Drug administration, 90, 92
Drug delivery, 90, 92, 93, 94, 95, 96, 97, 98, 99,
96, 97, 98, 99, 100, 102, 103, 197, 241,
244, 257
100, 102 , 103
E
Electroencephalography (EEG), 9,
Electromyography, 10, 201, 270
En erg y, 9, 27, 35, 37, 148 , 150, 153, 154, 155,
Environment, 19,
Epilepsy, 3, 5, 7, 8, 9, 10, 11, 12, 14, 18, 23, 29,
Exoskeleton, 314
34, 316
156, 159
75, 76, 97, 98, 101, 113, 128,
294, 295, 307
38, 39, 81, 84, 91, 95, 98, 100, 101,
112 , 204, 286
F
F1 score, 114, 119, 120, 176 , 207, 208, 209, 210,
Factor analysis, 262, 263
Feature extraction, 85, 86, 87, 114, 133, 14 8, 153,
Feature map, 115, 116, 117, 179, 180 , 181, 245,
Feature selection, 148, 162, 175, 17 7, 197, 199,
Filter methods, 205, 206
FMRI, 9, 22, 33, 34, 38, 72, 75, 82, 86–87, 123, 143,
Formulations, 26, 98, 153
Frequency domain feature, 149
271, 275, 276, 279, 286, 287, 291, 292,
301, 302, 307
159, 162, 166 , 176
204, 225, 243, 248, 262, 274, 297, 316
274, 299
203, 205, 206, 231, 270
174, 203, 204, 227, 243, 252, 291, 312
, 177, 199, 202, 203,
G
Gait analysis, 149, 150, 313, 314
Gene therapy, 11, 12, 14, 100, 102,
Generative Adversarial Networks (GANs), 82,
124, 125, 126, 127, 128, 129, 131,
132, 133, 134, 135, 136, 137, 138,
139, 140, 141, 142 , 143, 14 4, 231,
244, 251
Genetic disorders, 6, 10 0
Gradient motion nulling (GMN),
72, 73
Grey wolf optimizer, 297, 299, 300
Guillain-Barré syndrome, 7, 8
103
H
Healthcare, 23, 25, 26, 42, 45, 46, 47, 48, 49, 50,
Healthcare professionals, 49, 60, 61, 172 , 208,
Hemorrhage, 239
Huntington’s disease, 6, 7, 8, 10, 12, 10 0, 101,
Hyperparameter tuning, 175, 276
51, 52, 54, 55, 56, 59, 60, 61, 83, 86,
87, 101, 137, 141, 142, 14 4, 172 , 195,
196, 198, 208, 210, 213
219, 223, 232, 242, 258, 267
270, 292
286
, 214, 215, 216,
I
ICMR, 45, 46
Image registration, 2 51, 253
Image segmentation, 21, 143, 244, 252
Implants, 23, 39, 99, 103
Inammation, 6, 13, 91, 93
K
KNN, 222, 226, 227, 250, 259, 260, 263, 264,
265, 266, 267, 270, 271, 291, 314
L
Ligands, 96, 97, 102
Linear Discriminant Analysis (LDA),
Liposomes, 97, 98
Logistic regression,
Long Short Term Memory (LSTM), 110, 11 5,
Loss function, 28, 132, 170, 171, 276, 296
205, 206
114, 199, 207, 210, 222, 271,
287, 314
118, 120, 122, 176, 243, 244, 271
M
Machine learning, 11, 12, 20, 21, 37, 48, 49, 50,
Magnetic Resonance Imaging (MRI), 3, 34, 48,
Magnetoencephalography (MEG), 9, 34, 243
Mean Absolute Error (MAE), 209, 210
Mel-Frequency Cepstral Coefcients (MFCC),
Migraine, 7, 8, 12, 91, 112, 128
Mild Cognitive Impairment (MCI), 176, 223,
Mildly demented, 239, 240, 241
Mish activation function, 178, 179, 188
51, 55, 75, 83, 101, 109, 114, 122, 123,
220, 239, 312
49, 51, 69, 81, 90, 126, 149, 161, 168,
174, 196, 219, 239, 269, 291
148
226, 229, 243, 291, 296
Index 335
MLP (multilayer perceptron), 249, 250, 314
Model communication cost, 302, 304, 307
Monoclonal antibodies, 12, 95
Motion insensitive sequences, 73
MSE, 127, 128, 209, 210
Multiclass classication, 174, 175 , 291
Muscular dystrophy, 6, 7, 101
Mutations, 6, 7, 8, 100, 101, 103
N
Nanoparticles, 93, 96, 97, 98, 102
Nerves, 3, 8, 10, 98, 109, 111, 112 , 193, 243
Neural networks, 22, 28, 33, 37, 36, 39, 40, 41,
Neurocomputing, 19
Neurodisease, 22, 60, 243, 290
Neuroimaging, 9, 10, 14, 20, 21, 22, 26, 31, 33,
Neuroinformatics, 19, 21, 22, 38
Neurological disorders, 3, 5, 69, 77, 81, 83, 86,
Neurological procedures, 45
Neuropathy, 7, 8, 10
Neuropharmacology, 12
Neurorehabilitation, 26, 311
Neurotransmitters, 91
Noise reduction, 71, 72, 78, 133, 153, 163, 248,
Normalization, 115,
72, 82, 114 , 148, 149, 159, 162, 163,
166 , 171, 176, 197, 198, 199, 206, 207,
210, 211,
299, 294, 307, 313, 316
34, 40, 41, 57, 58, 73, 75, 81, 82, 83,
84, 85, 86, 87, 88, 90, 103, 124, 125,
126, 127, 128, 131, 132, 133, 134, 135,
136, 137, 138, 139, 140, 141, 142 , 143,
144 , 174, 175, 197, 200, 202, 203,
207, 212, 219, 220, 223, 226, 239
90, 91, 92, 93, 94, 96, 98, 100, 101,
109, 111, 113 , 114, 115, 117, 119, 121,
122, 123, 138, 139, 141, 142, 143, 14 4,
191, 239, 242, 254, 286
251, 253
180 , 182, 202, 252, 253, 299
220, 231, 232, 242, 243, 244,
204,
118, 153, 163, 164 , 168, 176 ,
Permeability, 90, 94, 95, 97
Personalized medicine, 14, 19, 23, 25, 26, 83,
Pervasive stigma, 242
Physical restraints, 74
Positron emission tomography, 9, 126, 174, 203,
Precision, 9, 25, 26, 32, 34, 41, 57, 58, 59, 84, 86,
Pretrained models, 176 , 244, 269, 270, 271, 272,
Principal Component Analysis (PCA), 197, 199,
Probabilistic neural network (PNN), 243, 248,
Probability, 27, 129, 130, 154, 171, 222, 226, 247,
Prognosis, 26, 86, 90, 142, 161, 200, 328
Proprioception, 322, 323, 324, 325, 326,
Prospective motion correction (PMC), 74
85, 90, 103, 143, 195, 211,
267
258,
219, 239, 292
87, 97, 99, 102, 114, 119, 120, 132,
133, 139, 148, 149, 150, 163, 175, 176,
196, 205, 207, 208, 209, 210, 213, 214,
254, 286, 287, 292, 293, 301, 312,
326, 328
275, 286, 287, 293
202, 205, 206,
228, 229, 231
249
248, 260
327, 328
220, 223, 224, 226,
R
Random forest, 114, 149, 177, 206, 210, 211, 221,
Recall, 207, 208, 209, 210
Receptors, 96, 97, 324
Recurrent neural network, 110 , 115, 117, 118, 120,
Regression, 114 , 181, 197, 198
Resnet, 110 , 115, 118, 120, 122, 177, 178, 17 9,
Risk, 91
RMSE, 209, 210
Robotic rehabilitation, 312, 314
270, 271, 292, 311, 313, 314
122, 245, 313
, 243, 244, 250
188, 251, 301, 302, 304, 305
O
Oasis dataset, 182, 183, 188 , 292
Omega-3 fatty acids, 13
P
Parkinson’s disease, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13,
14, 18, 23, 24, 55, 56, 90, 91, 193, 197,
211, 239, 257, 269, 271, 311, 312, 314 ,
315, 316
Pathogenesis, 90
Performance indices, 156
S
Sampler, 180, 181
Scapular dysfunction, 323
Schizophrenia, 32, 95, 239, 241, 242,
243, 254, 286
Sclerosis, 90, 257
Segmentation, 251, 252
Segnet, 291
Seizure disorders, 5
Sensorimotor, 39, 149, 324, 325, 328
Serotonin, 91
Signal processing, 28, 148
336 Index
Slice timing, 252
Smoking, 91, 92
Smoothing, 253, 254
Sparse coding, 133
Spatial transformer network, 174 , 178, 179, 180 ,
181, 182 , 184, 18 5, 186, 18 8
Speech biomarkers, 311
Statistical evaluation, 153
Stroke, 3, 4, 7, 8, 9, 11, 12, 13, 23, 38, 56, 82, 85,
87, 90, 91, 101
Stylegan, 131
Summation layers, 249
Supervised learning, 197, 198, 199, 206, 207,
209, 210, 211, 213, 215, 219, 220, 221,
222, 223, 224, 227, 231, 232, 257, 258,
259, 261, 267, 311
T
Targeted drug delivery, 90, 93, 95, 98,
99, 103
Time domain feature, 150
Tourette syndrome, 4
Transformer network, 188
Transient ischemic attacks, 7
Transporters, 94, 95, 96
Tu mor s, 92, 98, 99, 102
U
U-net, 133
Ultrasound, 94, 97
Unied Parkinson’s Disease Rating Scale
(UPDRS), 315
Unsupervised learning, 39, 133, 206, 219, 220,
221, 222, 223, 224, 228, 229, 231, 232
V
Variational encoders, 133
Vec tors, 93, 100
Virtual health assistants, 45, 50
Virtual reality, 312, 314 , 315
Visual geometry group-16 (VGG-16), 110, 114,
115, 118, 120, 122
W
Wasserstein GANs (WGAN), 131
Wavelet transform, 28, 71, 75, 199, 204
Wrapper methods, 205, 206
Z
Zolgensma, 11, 12, 102
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