tree [42].Figure 5.10 Categorization of social media data [43].Figure 5.11 Frame work for proposed system.Figure 5.12 Basic steps of page rank algorithm. https://www.analyticsvidhya.com/...Figure 5.13 Output generated after Pre processing step. Stop Word algorithm has ...Figure 5.14 (a) Pre processing; (b) Graph clustering.Figure 5.15 Apply k-mean algorithm.Figure 5.16 Generation of clustering data.Figure 5.17 Output of K-means algorithm.Figure 5.18 Apply back propagation algorithm.Figure 5.19 Result of clustering.Figure 5.20 Classified data.Figure 5.21 Performance comparison of proposed algorithm and other existing meth...Figure 5.22 Execution time.6 Chapter 6Figure 6.1 Bioinformatics tools used in cancer research.Figure 6.2 Cancer genomic databases based on bioinformatics.Figure 6.3 Procedure of SELDI-MS-TOF based on bioinformatics.
7 Chapter 7Figure 7.1 Big Data: 6 V’s.Figure 7.2 Google research trend IoT Health and Big Data Health.Figure 7.3 Big Data Flow from its sources to storage, analytics, and visualizati...Figure 7.4 Healthcare IoT system architectureFigure 7.5 Healthcare IoT monitoring architecture [10].
8 Chapter 8Figure 8.1 BSA saline droplets at different initial PBS concentrations (Ø): The ...Figure 8.2 (I–IV) shows the time evolution of the first-order statistical (FOS) ...Figure 8.3 (I–IV) show the comparison of the averaged gray level co-occurrence m...Figure 8.4 (I–IV) show the time evolution of the gray level co-occurrence matrix...Figure 8.5 The images of the dried films of BSA-saline are captured after 24 h a...Figure 8.6 Histograms depicting the counts of the pixels along the y-axis, and t...
9 Chapter 9Figure 9.1 Neural network architecture.Figure 9.2 Basic architecture of DNN.Figure 9.3 Basic structure of CNN.Figure 9.4 Basic structure of DBN.Figure 9.5 Basic architecture of RNN.Figure 9.6 Basic architecture of DA.Figure 9.7 Summary of the proposed model.
10 Chapter 10Figure 10.1 Percentages of data mining techniques applied to Alzheimer’s studies...Figure 10.2 Percentages of data mining techniques applied to Dementia’s studies ...Figure 10.3 Percentages of data mining techniques applied to depression studies ...Figure 10.4 Percentages of data mining techniques applied to Schizophrenia and b...
11 Chapter 11Figure 11.1 Image depicting prostate cancer cell segmentation (Source—Alan Parti...Figure 11.2 Basic neural network design.Figure 11.3 Various neural network architectures. (a) Recurrent Neural network, ...Figure 11.4 An illustration of a typical CNN architecture for pixel RGB images (...Figure 11.5 (a) Input Image, (b) Convolutional filter and (c) Convolved output v...Figure 11.6 Average versus max pooling with a stride of 2.Figure 11.7 Basic CNN architecture for image classification [55].Figure 11.8 Image denoising of brain MR image by DnCNN network [26].
12 Chapter 12Figure 12.1 TNM system of staging.Figure 12.2 Factors affecting cancer prognosis.Figure 12.3 Levels of medical imaging.Figure 12.4 General steps of image processing.Figure 12.5 Artificial intelligence tools are used for detection, characterizati...
13 Chapter 13Figure 13.1 Data mining process.Figure 13.2 Generic model of classification.Figure 13.3 Filter approach.Figure 13.4 Wrapper approach.Figure 13.5 Snapshot of classifiers in WEKA.Figure 13.6 Classifiers performance.
List of Tables
1 Chapter 1Table 1.1 Time series variables with description and physical units recorded in ...Table 1.2 Time series variables with physical units [30].Table 1.3 Comparison of different models during testing.
2 Chapter 2Table 2.1 Summary of database sources of protein structure classification.
3 Chapter 3Table 3.1 Comparison of Research paper for diabetes dataset.Table 3.2 Comparison of Research papers on hepatitis dataset.Table 3.3 PIMA diabetes dataset description.Table 3.4 Description of Hepatitis dataset’s attributes.Table 3.5 Difference between filter method and wrapper method.Table 3.6 Accuracy obtained in Task 1 for diabetes dataset.Table 3.7 Accuracy obtained in Task 1 for hepatitis dataset.Table 3.8 Accuracy obtained in Task 2 in diabetes dataset.Table 3.9 Accuracy obtained in Task 2 in hepatitis dataset.Table 3.10 Accuracy obtained by filter feature selection methods in diabetes dat...Table 3.11 Accuracy obtained by wrapper feature selection methods in diabetes da...Table 3.12 Accuracy obtained by filter feature selection methods in hepatitis da...Table 3.13 Accuracy obtained in wrapper feature selection methods in the hepatit...Table 3.14 Accuracy obtained in Task 4 for diabetes dataset.Table 3.15 Accuracy obtained in Task 4 for hepatitis dataset.Table 3.16 Conclusion table for diabetes dataset.Table 3.17 Conclusion table for hepatitis dataset.
4 Chapter 4Table 4.1 Healthcare 4.0’s application scenarios.
5 Chapter 5Table 5.1 Comparative analysis between proposed algorithm and other existing met...Table 5.2 Comparative analysis between proposed algorithm and other existing met...
6 Chapter 6Table 6.1 Types of biomarkers explained based on their utilization.Table 6.2 List of the biomarkers using bioinformatics tools.Table 6.3 The types of microarray explained with illustrations.
7 Chapter 7Table 7.1 Reviewed IoT healthcare system.
8 Chapter 8Table 8.1 Detailed report of Mann–Whitney U test for ASM (angular second moment)...Table 8.2 Detailed report of Mann–Whitney U test for COR (correlation) at each c...Table 8.3 Detailed report of Mann–Whitney U test for ENT (entropy) at each conce...Table 8.4 Detailed report of Mann–Whitney U test for IDM (inverse difference mom...
9 Chapter 9Table 9.1 Classification results for diabetic and non-diabetic patients and corr...
10 Chapter 10Table 10.1 Several study researches review in context to data mining techniques ...Table 10.2 Several study researches review in context to data mining techniques ...Table 10.3 Several study researches review in context to data mining techniques ...Table 10.4 Several study researches review in context to data mining techniques ...
11 Chapter 11Table 11.1 Advancements in tools of medical imaging.Table 11.2 Some supplementary advancements in the subcellular and cellular secti...Table 11.3 Some miscellaneous advancements in the organ section and multidomain ...
12 Chapter 12Table 12.1 Comparison between different imaging techniques.
13 Chapter 13Table 13.1 WEKA names of selected classifiers.Table 13.2 Feature section algorithms.Table 13.3 Features in the dataset.Table 13.4 Classification accuracy in % with original features.Table 13.5 Classification accuracy in % after GA-based features selection.Table 13.6 Classification accuracy in % after PSO-based features selection.
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