Handbook on Intelligent Healthcare Analytics

3 Chapter 6 Table 6.1Comparison of LR, ARIMA, and LSTM of MSE and RMSE.

4 Chapter 7 Table 7.1Results of learners.

5 Chapter 8 Table 8.1Dataset with cases.

6 Chapter 9 Table 9.1Knowledge security laws from numerous countries and organizations. Table 9.2Blockchain flexibility concerning threats.

7 Chapter 11 Table 11.1Comparison of different DNN architectures. Table 11.2Different gaps in CBIR systems [36].

8 Chapter 12 Table 12.1Characteristics details of COVID-19 in various organs [2]. Table 12.2AI methods and big data for health care sector.

9 Chapter 14 Table 14.1Performance of the various machine learning algorithms.

10 Chapter 15 Table 15.1Classification and prediction of customer data set. Table 15.2Clustering and association of customer data set.

11 Chapter 16 Table 16.1Classification of healthcare data for accurate multiple data integrit... Table 16.2Healthcare sample dataset for preprocessing and data fusion.

12 Chapter 17 Table 17.1Performance estimation for accuracy.

13 Chapter 18 Table 18.1Seizure detection based pre-processing, input formulation, feature ex... Table 18.2Details of normal, abnormal, and absence subject. Table 18.3Schematics of convolution layer. Table 18.4Schematics of GRU-SVM layers. Table 18.5p-value of a classification model.

1 Cover

2 Table of Contents

3 Title Page

4 Copyright

5 Preface

6 Begin Reading

7 Index

8 End User License Agreement

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Scrivener Publishing

100 Cummings Center, Suite 541J

Beverly, MA 01915-6106

Publishers at Scrivener

Martin Scrivener ( martin@scrivenerpublishing.com)

Phillip Carmical ( pcarmical@scrivenerpublishing.com)

Edited by

A. Jaya

Department of Computer Application, B.S. Abdur Rahman Crescent Institute of Science, Technology, Chennai, India

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