his volume demonstrates the diverse state-of-the-art applications that combine Artificial Intelligence with soft computing, which has great potential for creating smart personalized healthcare services. The book showcases the myriad uses of AI and computer techniques in healthcare that employ Deep Learning, robotics, Machine Learning, blockchain, emerging cloud, edge computing, Practical Byzantine Fault Tolerance consensus, CNN architecture, Splunk, genetic algorithms (GA), DurBhashan, and many more. These technologies can be used in healthcare for enhanced data sharing, remote health monitoring, tele-rehabilitation, connecting rural populations with healthcare services, identifying diseases and health issues, automated medical diagnosis, analyzing information in surgical videos, ensuring timely communication and transportation during health disasters and emergencies, for optimizing expenditures, and more.
Soft computing approaches like particle swarm optimization (PSO), genetic algorithm (GA); ANN (artificial neural networks) is effectively used for diagnosing and prediction of disease from healthcare data of genetics, physiology, radiology, and cardiology and neurology disciplines. AI and soft computing can be used to make smart personalized healthcare services to build next generation ultra-digital hospitals with complete AI methodology, robotic surgery, 5G infrastructure for remote assistance, etc. The scope of this book covers not only background related to AI but also state-of-the-art applications in AI and soft computing to achieve intelligent personalized healthcare services.
Chapter 1 covers how remote health monitoring systems can help patients get advice related to the required treatment from doctors. The first part of the module gives a brief idea and demonstration of systems with the help of an experimental setup using LabVIEW. The later part of the module covers how AI-IoMT can assist doctors in prescribing medicines in accordance with the patient’s critical parameters. This module also assesses numerous IoT security, privacy characteristics, various cyber threat models and attack classification.
Chapter 2 discusses the use of huge biomedical things data with emerging cloud and edge computing technologies to identify diseases with high accuracy. Chapter 3 emphasizes the accurate identification and diagnosis of disease using Artificial Intelligence and Machine Learning in today’s unpredictable world environment.
Chapter 4 presents an approach for accessing patient records using blockchain. This chapter deals with ways to enhance data-sharing application of the health sector and pharmacy that are built on concepts of hyper ledger fabric and practical Byzantine fault tolerance consensus. Chapter 5 discusses the various security issues and intelligent solutions for IoMT-enabled healthcare systems. This chapter covers a variety of security, privacy issues, and various attacks on smart devices, intrusion detection systems and intelligent solutions such as malware identification for safeguarding healthcare data.
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Chapter 18 proposes and analyzes an optimized reinforcement learning method in a disaster scenario and how this method is applied to reduce the loss of human life by ensuring timely communication and transportation among various units. Chapter 19 discusses the model for scheduling and allocation of healthcare resources as per patient’s physical activity needs. The model can be utilized to apply different scheduling algorithms and select the efficient ones to reduce waiting time of a patient.

lgli/Handbook of Research on AI and Soft Computing.pdf

lgrsnf/Handbook of Research on AI and Soft Computing.pdf

Uma N. Dulhare; A. V. Senthil Kumar; Amit Dutta; Seddik Bri; Ibrahiem M. M. El Emary

Uma N. Dulhare,A. V. Senthil Kumar,Amit Datta,Seddik Bri,Ibrahiem M. M. EI Emary

Apple Academic Press, Incorporated

Taylor & Francis Ltd

United Kingdom and Ireland, United Kingdom

CRC Press (Unlimited), OAKVILLE, 2023

Canada - English Language, Canada

producers:
Adobe PDF Library 15.0

This volume demonstrates the diverse state-of-the-art applications that combine artificial intelligence with soft computing, which has great potential for creating smart personalized healthcare services. The book showcases the myriad uses of AI and computer techniques in healthcare that employ deep learning, robotics, machine learning, blockchain, emerging cloud, edge computing, Practical Byzantine Fault Tolerance consensus, CNN architecture, Splunk, genetic algorithms (GA), DurBhashan, and many more. These technologies can be used in healthcare for enhanced data sharing, remote health monitoring, tele-rehabilitation, connecting rural populations with healthcare services, identifying diseases and health issues, automated medical diagnosis, analyzing information in surgical videos, ensuring timely communication and transportation during health disasters and emergencies, for optimizing expenditures, and more. Presents new applications, techniques, and algorithms in AI and soft computing for intelligent, such as deep learning, robotics, machine learning, blockchain, emerging cloud, edge computing, Practical Byzantine Fault Tolerance consensus, CNN architecture, Splunk, genetic algorithms, and more.
Cover 1
Half Title 2
Title Page 4
Copyright Page 5
AAP Advances in Artificial Intelligence and Robotics 6
Series Page 8
About the Editors 10
Table of Contents 14
Contributors 16
Abbreviations 20
Preface 24
Part I: Internet of Medical Things and Cloud Technologies in Healthcare 28
1. Artificial Intelligence-Enabled IoMT for Medical Application 30
2. Advancement in Healthcare by Cloud and Edge Computing 60
3. Disease Identification and Diagnosis Using Artificial Intelligence 76
4. An Approach for Accessing Patients Records Using Medical Suite Blockchain 100
5. Security Issues and Intelligent Solutions for IoMT-Enabled Healthcare Systems 118
Part II: Artificial Intelligence and Techniques in Healthcare Services 146
6. An AI-Driven Multi-Management System for Medical Resource Allocation Providing Personalized Healthcare Services 148
7. Prediction of Autistic Spectral Disorder Inflictions Among Children Using Reinforcement-Based Learning Approach 164
8. Reinforcement Learning for Automated Medical Diagnosis and Dynamic Clinical Regimes 196
9. Surgical Phase Recognition Using Videos: Deep Neural Network Approach 216
10. Wearable Sensor-Based Monitoring and Classification Using Deep Learning for Personalized Healthcare 236
11. Personalized Physio-Care System Using AI 256
12. An Approach for the Implementation of Multilevel Technique of GA for Cardiac Disease Detection 286
Part III: Telemedicine and Personalized Healthcare Services 304
13. A Tele-Healthcare System for Diagnosis and Treatment of Patients During a Pandemic 306
14. Personalized Telemedicine Utilizing Artificial Intelligence, Robotics, and Internet of Medical Things (IoMT) 328
15. Cyber-Physical System-Based Secure Online Medication System 352
16. DurBhashan: A Healthcare Guiding Booth for Rural People 376
17. Internet Pharmacy Branch in Poland and Its Logistics Support Management 402
18. Effective Emergency Transportation and Communication for Saving Human Lives During Disaster 428
19. Resource Allocation and Scheduling of Patient’s Physical Activity Using PSO 454
Index 474
Intelligent,Systems;,Medical,Devices
Intelligent Systems,Medical Devices

2024-01-11