Page 303 - Handbook of Deep Learning in Biomedical Engineering Techniques and Applications

294 Index

Blockchain (BC) technology European credit transfer and Computer vision, 274e283
(Continued) accumulation system Continuous bag of words
Consortium blockchain, (ECTS), 101e103 (CBOW), 139e141, 140f
89e90 high-level architecture, 86f Conventional models, 168e169
cryptographic function, lifelong learning, 101e103 ConvNet, 71
100e101 massive open online courses Convolutional Architecture for
data ledger layer, 86e87 (MOOCs), 101e103 Fast Feature Embedding
Digital Ledger Technology peer-to-peer (P2P) network (CAFFE), 67
(DLT), 110 layer, 85, 88 features, 67
directed acyclic graph (DAG) permissioned/private, 89 theano, 68
approaches, 98e103 permissionless/public, 89 torch tool, 68
double spending attacks, secure hash algorithm (SHA- Convolutional neural network
104e105 256), 86e87 (CNN), 161e167, 162f,
education domain smart contracts, 88 248f, 249
accountability, 112e113 structure, 87f AlexNet, 162e163, 163f
addressing space, 112 transaction, 99f application, 37e50
collaborative learning vote-based approaches, 96e97 abdomen, 38te47t,
management, 114 delegated byzantine fault 49e50
copyrights management/IP tolerance (dBFT), 97 brain, 37, 38te47t
management, 115 federated byzantine breast, 38te47t, 48
credit earning, 114 agreement, 97 cardiac image analysis,
data integrity, 112 practical byzantine fault 38te47t, 49
decentralized control, 113 tolerance (PBFT), 96, 96t chest, 38te47t, 49
digital academic certificate simplified byzantine fault eye, 38te47t, 48
management, 114 tolerance (SBFT), 97 architectures, 34e37
digital identity, 112e113 Blockchain (BC) technology biomedicine, 250e251
examination review, 115 scalability challenges, ConvNet, 71
fault tolerance, 113 115e117 convolution layer, 249e250,
globalization education, block size, 115 250f
114 hypergraph-based convolution layerekernel, 74,
immutability, 113 partitioning, 117 74f
learning contract, 114 offchain, 115e116 fully convolutional layer, 250
learning engagement, 114 security challenges, 117 future work, 50e51
learning outcomes Brain, body, and machine general architecture, 34f
management, 114 interface, 258 general classification
library books return, 114 Brainemachine interface, 258 architectures, 34e35
lifelong learning, 115 classification, 258 input image, 73
MOOCs, 114 invasive techniques, 259 limitations, 50e51
parents’ consents, 115 Broad gateway protocol (BGP) medical imaging and
registry/ledger, 113 hijacks, 108 healthcare, 50e51, 51f
removing third-party risks, multistream architectures,
113 Color fundus imaging (CFI), 48 35e36
self-sovereignty, 113 Computed tomography (CT) pooling layer, 33, 250
smart contracts, 113 images, 273 recurrent neural network
tracking issue, 114 Computer-aided diagnosis, (RNN), 75e79
transparency, 113 26e27 advantages, 78
trust and provenance, Computer-aided system, architecture, 78f
113 detection/diagnosis, disadvantages, 79
university system, 112f 31e32 ResNet, 164e167, 165fe166f