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List of Tables
Оглавление1 Chapter 2Table 2.1 Sample Dataset for Phase-I.Table 2.2 Accuracy of the modelTable 2.3 Precision of the model.Table 2.4 Recall of the model.Table 2.5 F1-score of the model.
2 Chapter 4Table 4.1 Sample rule set for the proposed expert system.
3 Chapter 5Table 5.1 Description of network architecture.Table 5.2 Description of the hyper parameters.
4 Chapter 6Table 6.1 Comparison of existing software apps.Table 6.2 Comparison of previous approaches.Table 6.3 Comparison of various DCNNs.
5 Chapter 7Table 7.1 Examples of some types of ontologies.
6 Chapter 8Table 8.1 Age & Gender of Subjects.Table 8.2 Percentage of Correct Answers in AB task and α of subjects according t...
7 Chapter 9Table 9.1 Electrical properties of human tissue.Table 9.2 Dataset creation.Table 9.3 Tabular representation of Classification Reports using KNN, Decision T...
8 Chapter 10Table 10.1 Performance of SA on drug reviews using ML models.
9 Chapter 11Table 11.1 Classification report of our machine learning model.Table 11.2 Summary of hyper parameter tuning.
10 Chapter 12Table 12.1 Classification Report.
11 Chapter 13Table 13.1 Causes and symptoms for pneumothorax, pneumonia, pleural effusion and...Table 13.2 Causes and symptoms for nodule, mass, cardiomegaly, edema and consoli...Table 13.3 Causes and symptoms for pleural thickening, infiltration, fibrosis an...Table 13.4 Comparison of true label and predicted label for various diseases.
12 Chapter 14Table 14.1 Difference between acute stage and chronic stages of leukemia.
13 Chapter 16Table 16.1 Patient’s condition for decision making.
14 Chapter 17Table 17.1 Sample covid-19 patient details with different age group.
15 Chapter 18Table 18.1 Related work table.
16 Chapter 19Table 19.1 COVID-19 Dataset Sample.Table 19.2 Sample of risk wise performance comparison of actual vs predicted inf...Table 19.3 Sample of Rule Base Generation from Decision Tree.Table 19.4 Classification of Countries based on Decision Tree Rule Generation.Table 19.5 Cluster Groups of k-means Clustering Algorithm.Table 19.6 Classification accuracy of proposed algorithms.Table 19.7 Sample of classification of countries based on output variables.Table 19.8 Risk measurement of output variables.Table 19.9 Sample of classification of countries based on risk measurement.
17 Chapter 20Table 20.1 Values of km and kv.
18 Chapter 21Table 21.1 Performance measures of different wavelet by Modified-Random Forest c...Table 21.2 Accuracy comparison with db4 feature extraction using modified RF alg...Table 21.3 Comparison of accuracy of db4 feature extraction with different class...Table 21.4 Comparison of accuracy of MFCC feature extraction with different clas...
19 Chapter 22Table 22.1 Quantitative analysis of the proposed model and the benchmark model.Table 22.2 Number of trainable parameters in the benchmark and the proposed mode...
20 Chapter 23Table 23.1 Statistical texture features.Table 23.2 Number of features in each combination of feature vectors used.Table 23.3 Average recall for the variants of feature sets.Table 23.4 Average precision for the variants of feature sets.Table 23.5 Average accuracy for the variants of feature sets.Table 23.6 Confusion matrix for the four classes using SVM.Table 23.7 SCC detection performance for SVM.
21 Chapter 24Table 24.1 Grade features decision [11].Table 24.2 Accuracy comparison of various classifiers by using different paramet...Table 24.3 Performance measures of different classifiers in terms of TPR, TNR, a...Table 24.4 Results of accuracy, precision, and recall from two different dataset...Table 24.5 Performance of the individual field-specific DCNNs in terms of AUC.
