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1 Chapter 2Table 2.1 Variables description.Table 2.2 Bivariate logistic regression with AOR to distribution of child alive ...Table 2.3 Ranked Boruta features importance result.Table 2.4 Data imbalance sampling technique result.Table 2.5 Comparing sampling method.Table 2.6 Performance of Naïve Bayes classifier.Table 2.7 Performance of C5.0 classifier.Table 2.8 Confusion Matrix of SVM Imbalanced data.Table 2.9 Performance of SVM on prediction on imbalanced data.Table 2.10 Confusion Matrix for SVM balanced data.Table 2.11 Performance of SVM on prediction on balanced data.Table 2.12 Performance of Random Forest classifier.Table 2.13 10-fold cross-validation on imbalance target data.Table 2.14 10-fold cross-validation on balance target data.

2 Chapter 3Table 3.1 Individual’s demographics and their dementia status.Table 3.2 Basic characteristics’ of MRI with Clinical Dementia Rating (CDR).Table 3.3 Descriptive quantitative variables (n = 373).Table 3.4 Actual vs Predicted.Table 3.5 Accuracies of different algorithms.Table 3.6 Training status.Table 3.7 Comparison of transfer learning pretrained CNN learners.

3 Chapter 4Table 4.1 Comparison of proposed method [18] with other segmentation methods usi...Table 4.2 The results of OC segmentation of proposed method [34] using a differe...

4 Chapter 5Table 5.1 Several soft technologies to fulfil various objectives.Table 5.2 Several examples of AI and ML approaches in healthcare.Table 5.3 Information of cancer disease with approaches and dataset.Table 5.4 Various big data analytics tools with functionalities.

5 Chapter 7Table 7.1 Notations used in the proposed algorithms.

6 Chapter 9Table 9.1 Dataset description.Table 9.2 Regional and provincial data are also presented in Table 9.2.

7 Chapter 11Table 11.1 Adoption index for ‘ologies’.