Emerging Technologies for Healthcare

"Emerging Technologies for Healthcare" begins with an IoT-based solution for the automated healthcare sector which is enhanced to provide solutions with advanced deep learning techniques.

The book provides feasible solutions through various machine learning approaches and applies them to disease analysis and prediction. An example of this is employing a three-dimensional matrix approach for treating chronic kidney disease, the diagnosis and prognostication of acquired demyelinating syndrome (ADS) and autism spectrum disorder, and the detection of pneumonia. In addition, it provides healthcare solutions for post COVID-19 outbreaks through various suitable approaches, Moreover, a detailed detection mechanism is discussed which is used to devise solutions for predicting personality through handwriting recognition; and novel approaches for sentiment analysis are also discussed with sufficient data and its dimensions.

This book not only covers theoretical approaches and algorithms, but also contains the sequence of steps used to analyze problems with data, processes, reports, and optimization techniques. It will serve as a single source for solving various problems via machine learning algorithms.

Autorentext

Monika Mangla, received her PhD from Thapar Institute of Engineering & Technology, Patiala, Punjab, in 2019. Currently, she is working as an assistant professor in the Department of Computer Engineering at Lokmanya Tilak College of Engineering (LTCoE), Navi Mumbai.

Nonita Sharma is working as assistant professor, National Institute of Technology, Jalandhar. She received the B. Tech degree in Computer Science Engineering in 2002, the M. Tech degree in Computer Science engineering in 2004, and her PhD degree in Wireless Sensor Network from the National Institute of Technology, Jalandhar, India in 2017.

Poonam Mittal received her PhD from J.C Bose University of Science and Technology YMCA, Faridabad, India, in 2019. Currently, she is working as an assistant professor in the Department of Computer Engineering at J.C Bose University of Science and Technology YMCA, Faridabad, India.

Vaishali Mehta Wadhwa obtained her PhD in Facility Location Problems from Thapar University. Her research interests include approximation algorithms, location modeling, IoT, cloud computing and machine learning. She has multiple articles and 2 patents to her name.

Thirunavakkarasu K. is a distinguished academician with over twenty-two years of experience in teaching and working in the software industry. Curently, he is heading the Department of BCA and Specialization at Galgotias University. He has done Bachelor in computer science from the University of Madras in 1994 and received 3 master's degrees in computer science.

Shahnawaz Khan is an assistant professor and serving as Secretary-General of Scientific Research Council at University College of Bahrain. He holds a PhD (Computer Science) from the Indian Institute of Technology (BHU), India.

Klappentext

The book aims to devise new machine learning paradigms to address prevalent challenges in the field of healthcare from multiple perspectives. Internet of Things (IoT) refers to the computer network consisting of 'things' or physical objects. These things comprise sensors or software or a method to connect and exchange data with other devices. This book, Emerging Technologies for Healthcare, focuses primarily on the use and applications of IoT and deep learning approaches for providing automated healthcare solutions. It gives insightful information of data and provides feasible solutions through various approaches of machine learning and its applicability to disease analysis and prediction. An example of this is employing a three-dimensional matrix approach for treating chronic kidney disease, the diagnosis and prognostication of acquired demyelinating syndrome (ADS) and autism spectrum disorder, and the detection of pneumonia. In addition to this, providing healthcare solutions for post COVID-19 outbreaks through various suitable approaches is also highlighted. Furthermore, a detailed detection mechanism is discussed which is used to come up with solutions for predicting personality through handwriting recognition; and novel approaches for sentiment analysis are also discussed with sufficient data and its dimensions. This book covers not only theoretical approaches and algorithms, but also contains a sequence of steps to analyze problems with data, process, reports, and optimization techniques. The book serves to be a single source for various problem-solving by machine learning algorithms. It begins with IoT-based solutions for the automated healthcare sector and extends to providing solutions of deep learning as an advanced technology. Audience
The book will be used by research scholars, engineers, IT professionals, IT manufacturing industries involved in the associated healthcare fields, network administrators, health care practitioners, cybersecurity experts, and government research agencies.

Zusammenfassung
Emerging Technologies for Healthcare begins with an IoT-based solution for the automated healthcare sector which is enhanced to provide solutions with advanced deep learning techniques.

The book provides feasible solutions through various machine learning approaches and applies them to disease analysis and prediction. An example of this is employing a three-dimensional matrix approach for treating chronic kidney disease, the diagnosis and prognostication of acquired demyelinating syndrome (ADS) and autism spectrum disorder, and the detection of pneumonia. In addition, it provides healthcare solutions for post COVID-19 outbreaks through various suitable approaches, Moreover, a detailed detection mechanism is discussed which is used to devise solutions for predicting personality through handwriting recognition; and novel approaches for sentiment analysis are also discussed with sufficient data and its dimensions.

This book not only covers theoretical approaches and algorithms, but also contains the sequence of steps used to analyze problems with data, processes, reports, and optimization techniques. It will serve as a single source for solving various problems via machine learning algorithms.

Inhalt

Preface xvii

Part I: Basics of Smart Healthcare 1

**1 An Overview of IoT in Health Sectors 3
**Sheeba P. S.

1.1 Introduction 3

1.2 Influence of IoT in Healthcare Systems 6

1.2.1 Health Monitoring 6

1.2.2 Smart Hospitals 7

1.2.3 Tracking Patients 7

1.2.4 Transparent Insurance Claims 8

1.2.5 Healthier Cities 8

1.2.6 Research in Health Sector 8

1.3 Popular IoT Healthcare Devices 9

1.3.1 Hearables 9

1.3.2 Moodables 9

1.3.3 Ingestible Sensors 9

1.3.4 Computer Vision 10

1.3.5 Charting in Healthcare 10

1.4 Benefits of IoT 10

1.4.1 Reduction in Cost 10

1.4.2 Quick Diagnosis and Improved Treatment 10

1.4.3 Management of Equipment and Medicines 11

1.4.4 Error Reduction 11

1.4.5 Data Assortment and Analysis 11

1.4.6 Tracking and Alerts 11

1.4.7 Remote Medical Assistance 11

1.5 Challenges of IoT 12

1.5.1 Privacy and Data Security 12

1.5.2 Multiple Devices and Protocols Integration 12

1.5.3 Huge Data and Accuracy 12

1.5.4 Underdeveloped 12

1.5.5 Updating the Software Regularly 12

1.5.6 Global Healthcare Regulations 13

1.5.7 Cost 13

1.6 Disadvantages of IoT 13

1.6.1 Privacy 13

1.6.2 Access by Unauthorized Persons 13

1.7 Applications of IoT 13

1.7.1 Monitoring of Patients Remotely 13

1.7.2 Management of Hospital Operations 14

1.7.3 Monitoring of Glucose 14

1.7.4 Sensor Connected Inhaler 15

1.7.5 Interoperability 15

1.7.6 Connected Contact Lens 15

1.7.7 Hearing Aid 16

1.7.8 Coagulation of Blood 16

1.7.9 Depression Detection 16

1.7.10 Detection of Cancer 17

1.7.11 Monitoring Parkinson Patie…