Exploration of artificial intelligence and blockchain technology in smart and secure healthcare / Arvind K. Sharma [and three others].

Format:

Book

Author/Creator:

Sharma, Arvind K., author.

Series:

Advances in Computing Communications and Informatics Series

Language:

English

Subjects (All):

Neural networks (Computer science).

Physical Description:

1 online resource (316 pages)

Edition:

First edition.

Place of Publication:

Singapore : Bentham Science Publishers, [2024]

Summary:

This book offers in-depth reviews of different techniques and novel approaches of using blockchain and artificial intelligence in smart healthcare services. The volume brings 14 reviews and research articles written by academicians, researchers and industry professionals to give readers a current perspective of smart healthcare solutions for medical and public health services. The book starts with examples of how blockchain can be applied in healthcare services such as the care of osteoporosis patients and security. Several chapters review AI models for disease detection including breast cancer, colon cancer and anemia. The authors have included model design and parameters for the benefit of professionals who want to implement specific algorithms. Furthermore, the book also includes chapters on IoT frameworks for smart healthcare systems, giving readers a primer on how to utilize the technology in this sector. Additional use cases for machine learning for gesture learning. COVID-19 management, and sentiment analysis. Readership Academic, professional, and students affiliated institutions involved in digital transformation in the healthcare sector.

Contents:

Cover

Title

Copyright

End User License Agreement

Contents

Preface

List of Contributors

Blockchain Associated Machine Learning Approach for Earlier Prognosis and Preclusion of Osteoporosis in Elderly

Kottaimalai Ramaraj1, Pallikonda Rajasekaran Murugan1,*, Gautam Amiya1, Vishnuvarthanan Govindaraj2, Muneeswaran Vasudevan1, Thirumurugan3, Yu-Dong Zhang4, Sheik Abdullah1 and Arunprasath Thiyagarajan2

INTRODUCTION

Related Studies

METHODOLOGY IN THE PROPOSED WORK

Principal Component Analysis (PCA)

Weighted kNN

Proposed PCA-wkNN

Dataset Description

Implementation and Results

CONCLUSION AND FUTURE SCOPE

REFERENCES

Online Detection of Malnutrition Induced Anemia from Nail Color using Machine Learning Algorithms

K. Sujatha1,*, Victo Sudha George2, NPG. Bhavani3, T. Kalpatha Reddy4, N. Kanya5 and A. Ganesan6

RELATED STUDIES

OBJECTIVES AND NOVELTY OF THE PROPOSED WORK

Scientific Significance

Gaps to be Covered through Proposed Work

Technical Solution

Methodology

Results and Discussion

Comparison of the System Taken up for Development Generated by AI.

Notes:

Includes bibliographical references.

Description based on publisher supplied metadata and other sources.

Part of the metadata in this record was created by AI, based on the text of the resource.

Description based on print version record.

ISBN:

9789815165432

9815165437

OCLC:

1432587100