Tele-Healthcare

Applications of Artificial Intelligence and Soft Computing Techniques

R. Nidhya, Manish Kumar, S. Balamurugan

• Publisher: Wiley-Scrivener
• Year: 2022
• Print ISBN: 9781119841760
• eBook ISBN: 9781119841920
• Edition: 1
• Topic: Computer Science
• Subtopic: Artificial Intelligence (AI) & Semantics
• Index: Computer Science

TELE-HEALTHCARE

This book elucidates all aspects of tele-healthcare which is the application of AI, soft computing, digital information, and communication technologies, to provide services remotely and manage one's healthcare.

Throughout the world, there are huge developing crises with respect to healthcare workforce shortages, as well as a growing burden of chronic diseases. As a result, e-health has become one of the fastest-growing service areas in the medical sector. E-health supports and ensures the availability of proper healthcare, public health, and health education services at a distance and in remote places. For the sector to grow and meet the need of the marketplace, e-health applications have become one of the fastest growing areas of research. However, to grow at a larger scale requires the following:

• The availability of user cases for the exact identification of problems that need to be visualized.
• A well-supported market that can promote and adopt the e-health care concept.
• Development of cost-effectiveness applications and technologies for successful implementation of e-health at a larger scale.

This book mainly focuses on these three points for the development and implementation of e-health services globally.

In this book the reader will find:

• Details of the challenges in promoting and implementing the telehealth industry.
• How to expand a globalized agenda of personalized telehealth in integrative medical treatment for disease diagnosis and its industrial transformation.
• How to design machine learning techniques for improving the tele-healthcare system.

Audience

Researchers and post-graduate students in biomedical engineering, artificial intelligence, and information technology; medical doctors and practitioners and industry experts in the healthcare sector; healthcare sector network administrators.

Table of contents

• Cover
• Half-Title Page
• Series Page
• Title Page
• Copyright Page
• Contents
• Preface
• 1 Machine Learning–Assisted Remote Patient Monitoring with Data Analytics
• 2 A Survey on Recent ComputerAided Diagnosis for Detecting Diabetic Retinopathy
• 3 A New Improved Cryptography Method-Based e-Health Application in Cloud Computing Environment
• 4 Cutaneous Disease Optimization Using Teledermatology Underresourced Clinics
• 5 Cognitive Assessment Based on Eye Tracking Using Device-Embedded Cameras via Tele-Neuropsychology
• 6 Fuzzy-Based Patient Health Monitoring System
• 7 Artificial Intelligence: A Key for Detecting COVID-19 Using Chest Radiography
• 8 An Efficient IoT Framework for Patient Monitoring and Predicting Heart Disease Based on Machine Learning Algorithms
• 9 BABW: Biometric-Based Authentication Using DWT and FFNN
• 10 Autism Screening Tools With Machine Learning and Deep Learning Methods: A Review
• 11 Drug Target Module Mining Using Biological Multifunctional Score-Based Coclustering
• 12 The Ascendant Role of Machine Learning Algorithms in the Prediction of Breast Cancer and Treatment Using Telehealth
• 13 Remote Patient Monitoring: Data Sharing and Prediction Using Machine Learning
• 14 Investigations on Machine Learning Models to Envisage Coronavirus in Patients
• 15 Healthcare Informatics: Emerging Trends, Challenges, and Analysis of Medical Imaging
• Index
• Also of Interest
• EULA