Page 290 - Big Data Analytics for Intelligent Healthcare Management

Index 285

off-chain data storage, 217 Chan-Vese (CV) technique, 30
online access to longitudinal data, 217 Chemical carcinogenicity, 154
prerequisites, 206 Chronic migraine (CM), 95
research and development, 215 Chronic obstructive pulmonary disease (COPD), 48
smart ecosystem, 212 Chronic tension type headache (CTTH), 95
transaction counter, 205 Clinical data, 45
transaction data, 205 Cloud computing, 1, 248
types of, 204f, 206 healthcare data optimization, 197–198
versions of, 202 and IoT-based health monitoring system
working principle of, 206, 207f act/notify module, 181–183, 182f
Bluetooth Low Energy, 179 Adafruit cloud registration process, 180–181, 187–189,
Borda method, 272–273 187–188f
Breast cancer tissue image classification, ConvNets application layer, 179
accuracy ranges, 60 body temperature data storage, 189–191, 194f
architecture, 61, 62f body temperature reading, 183–184, 184f, 189, 189–192f
dataset and methodologies detecting layer, 179
BreaKHis image dataset, 59–60, 61f fetch module, 179–180, 180f
convolution layer, 61 health data, 179
dimensionality reduction, PCA algorithm, 59–60, 62–63 heart rate, 183, 184f
fixed feature extractor, 62, 63f ingest module, 180, 181f
fully connected layer, 61 live body temperature reading in screen, 189, 193f
K-NN algorithm, 59–60, 64, 65f medicinal services framework, 178
logistic regression, 59–60, 63 pulse rate graph, 184, 186f
pooling layer, 61 raw pulse rate value, 184, 185f
SVM, 59–60, 64, 64f retrieve module, 181, 181f
transfer learning, 62 temperature reading on serial monitor, 183–184, 184f
10-fold cross validation accuracy, 67, 68t total feed of temperature reading, 189, 193f
implementation transport layer, 179
classification, 67 NAS, 33
dimensionality reduction, PCA algorithm, 66, 67t PaaS, SaaS, IaaS, HaaS, 33–34
feature extraction, 66, 66t Cloud data centers (CDCs), 13
hyperparameter tuning, 67 Cloudera Oryx, 21
Python programming language, 66 Cluster analysis, 152
proposed model, 64–65, 65f Clustering, 9–10, 232
test performance, LR, SVM, and K-NN Collaborative filtering (CF) recommendation system, 230–231f
40 data, 71–73 e-commerce websites, use in, 230
100 data, 73–76 HRS, 242
200 data, 77–80 memory-based collaborative filtering, 231
400 data, 80–82 model-based collaborative filtering, 232
validation accuracy, LR, SVM, and K-NN recommendation and prediction, 231
best validation accuracy, 69, 70t Compound annual growth rate (CAGR), 200–201, 203–205
40 data, 67, 68f Consensus algorithm, blockchain, 205t, 206
100 data, 68, 69f Consumable massive facts analytics, 19–20
200 data, 68, 69f Container as a service (CaaS), 14
400 data, 69, 70f Content-based filtering technique, 229
performance on test set, 69–70 Convolution neural networks (CNNS/ConvNets). See Breast
Burst IQ, 220 cancer tissue image classification, ConvNets
Cosine-based similarity measures, 232
Couchbase, 9–10
CouchDB, 248
C
CaaS. See Container as a service (CaaS) Counterfeit drugs, 216
CARE, 49 Cryptocurrencies, 15
Cassandra, 9–10, 53, 240 Cuckoo search optimization (CO) algorithm, 4
Cat swarm optimization (CSO) algorithm, 6 Cybersecurity, 213–214