Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics. Группа авторов

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      1 Chapter 1Figure 1.1 Big data in healthcare.Figure 1.2 Five vs of big data.Figure 1.3 Areas of big data analytics in medicine.

      2 Chapter 2Figure 2.1 Overall of missing values.Figure 2.2 Boruta features importance result.Figure 2.3 Top twenty features ranked by random forest.Figure 2.4 Class distribution before applying sampling techniques.Figure 2.5 C5.0 rule-based decision tree.

      3 Chapter 3Figure 3.1 Human brain and neurons.Figure 3.2 Brain atrophy variations of T1 (longitudinal relaxation time), (a) at...Figure 3.3 Extracting volume of brain by image processing.Figure 3.4 Structural MRI images representing different AD stages. (a) Mild deme...Figure 3.5 Age vs demented and non-demented.Figure 3.6 MMSE.Figure 3.7 nWBV.Figure 3.8 eTIV.Figure 3.9 ASF.Figure 3.10 AGE.Figure 3.11 EDUC.Figure 3.12 Non demented, demented and converted demented MRI count.Figure 3.13 Polynomial regression of SES and EDUC.Figure 3.14 Features to be used.Figure 3.15 Ensemble learning.Figure 3.16 Random forest tree of early Alzheimer’s detection.Figure 3.17 Confusion matrix.Figure 3.18 Pre-processing Transverse. (a) Raw/original image. (b) Skull-strippi...Figure 3.19 Smoothing of a Raw MR Imaging.Figure 3.20 Alzheimer’s 4-class images information.Figure 3.21 Classification objective.Figure 3.22 Fully connected CNN.Figure 3.23 Flowchart of proposed model.Figure 3.24 8-layered AlexNet architecture.Figure 3.25 VGG16 architecture with 16 layers.Figure 3.26 Inception module.Figure 3.27 GoogLeNet.Figure 3.28 ResNet architecture with skip connections running parallel.Figure 3.29 MobileNetV2 architectural representation.Figure 3.30 Neural СКАЧАТЬ