Page 292 - Big Data Analytics for Intelligent Healthcare Management

Index 287

Emotional fulfillment, 95 N-most active-based feature, 166, 169t
Encryption, 35 ROI-based features, 164, 166–167t
End-clients, 179 subject-dependent experiments on PS+SP
Enterprise data hub (EDH), 48 all features, 160–161, 160t
Epigenetics, 250 average ROI based feature, 161–162, 162t
Episodic migraine (EM), 95 N-most active-based feature, 162, 162t
Espressif8266 (ESP8266), 180, 181f N-most active ROI-based feature, 162, 163t
Euclidean distance, 7, 60, 276 ROI-based features, 161, 161t
Evolutionary algorithms, big data analytics, 4–5 train test dataset, 158–159
Evolutionary strategy (ES) algorithm, 4 Fuzzy C-means (FCM) clustering algorithm, 270–271
Extract transform load (ETL) process, 248 cluster center, 274
disadvantages, 274
FCM-KA method, biomedical data analysis
F
cluster analysis using optimal cluster centers, 274, 276
Facts mining algorithms, 21
objective function values and accurateness, 277
False negative rate (FNR), 70
obtaining optimal cluster centers, 274–276, 275f
False positive rate (FPR), 70
vs. standard techniques, average accuracy, 277–278,
Fault tolerance, 10
278t, 278f
Feature selection method, 153
statistical validity, 278, 279t
Filtering techniques, recommendation system, 230f
fuzziness factor, 274
collaborative-based filtering technique, 230–233
fuzzy membership function, 274
content-based filtering technique, 229
objective function, 274
hybrid filtering technique, 230
partition matrix, 274
Fingerprinting methods, 154
Firefly swarm optimization (FSO) algorithm, 6
Fish swarm optimization (FSW) algorithm, 6
G
F-measure, 234, 240
Gaussian classification technique, 155
Fog computing, 10
Gem Health, 220
F-ratio based method, 153
Gene cards, 253
Friedman rank test, 278, 279t
General adaptation syndrome, 91, 92f
FSO algorithm-based hybrid (FSOH) approach, 6
General Data Protection Regulation (GDPR), 218–221
FSO and SA-based hybrid (FSOSAH) technique, 4
Genetic algorithm (GA), 4, 256–257
Functional magnetic resonance imaging (fMRI), 151–154
Genetic programming (GP) algorithm, 4
BOLD and combined BOLD level, 156
Genomes, 221
dataset, 157
Genomic data, 45
experimental results, PS and SP, 159–160
Global System for Mobile Communication (GSM), 176
high spatial and temporal resolution, 151
Gradient-boosting decision tree (GBDT), 154–155
independent component analysis, 156–157
Grid computing, 29
k-fold cross validation, 158–159
Group search optimization (GSO) algorithm, 7
logistic/sigmoid function, 153
GSR and EMG biofeedback therapy. See EMG and GSR
maximum likelihood, 153
biofeedback therapy, chronic TTH stress
methodology, 157–158
Guard time, 220
neuroimaging technique, 152
GWAS, 253
preprocessing stages, 156
result analysis
subject-dependent results, 166, 171t H
subject-independent experiment, 166–170, 171t Hadoop, 28, 93, 248
spatial mixture modeling, 156–157 Apache Hadoop, 28–29
strokes patients, 156 HDFS, 28, 37, 49, 52
subject-dependent experiments on PS and SP datasets, 163, MapReduce, 28, 33
163–164f, 164–165t Hadoop-distributed file system (HDFS), 28, 37, 49, 52
average ROI-based feature, 164–165, 168t Hadoop user experience (HUE), 14
most active ROI-based feature, 166, 170t Hbase, 9–10