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chapter topics.Figure 5.2 Tools or methods for multi‐omics data analysis.

      5 Chapter 6Figure 6.1 Super learner concept diagram (Kabir and Ludwig, 2019).Figure 6.2 Scatter plot of the five rules for breast cancer patients in the ...Figure 6.3 Scatter plot of five rules for individuals with breast cancer fro...Figure 6.4 Scatter plot of 23 rules for breast cancer patients in the non‐Hi...

      6 Chapter 7Figure 7.1 Block diagram of the proposed method for the automatic identifica...Figure 7.2 An illustration of two class rough hypercuboids, considering the ...Figure 7.3 Comparative performance analysis of the proposed method and its v...Figure 7.4 Comparative performance analysis between the proposed method and ...Figure 7.5 Comparative performance analysis between the proposed method and ...Figure 7.6 Comparative performance analysis of the proposed and existing app...

      7 Chapter 8Figure 8.1 Architecture of a simple neural network.Figure 8.2 Architecture of a convoluted neural network model.Figure 8.3 Performance of implemented networks with varying optimizers.Figure 8.4 Accuracy obtained by optimizers in a convolutional neural network...Figure 8.5 Number of epochs required for training by CNN optimizers with ear...

      8 Chapter 9Figure 9.1 Anatomy of the human brain.Figure 9.2 MRI of a brain tumor.Figure 9.3 Support vector machine.Figure 9.4 Artificial neurons.Figure 9.5 Back‐propagation neural network.Figure 9.6 Random forest classifier.Figure 9.7 Flow chart of the proposed method.Figure 9.8 Original and resulting images with the bounding box.Figure 9.9 Splitting the whole image into LHS and RHS along the middle sagit...Figure 9.10 Stratified k‐fold cross validation.Figure 9.11 Structure of a confusion matrix.Figure 9.12 Accuracy of proposed and existing methods.

      Guide

      1  Cover Page

      2  Table of Contents

      3  Title Page

      4  Copyright

      5  Dedication

      6  Begin Reading

      7  Index

      8  Wiley End User License Agreement

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