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Dynamics of swarm intelligence health analysis for the next generation

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Dynamics of swarm intelligence health analysis for the next generation/ edited by Suresh Kumar Arumugam, Utku Kose, Sachin Sharma, Jerald Nirmal Kumar S.
其他作者:	Kumar Arumugam, Suresh,
出版者:	Hershey, Pennsylvania :IGI Global, : 2023.,
面頁冊數:	1 online resource (273 p.)
內容註:	Chapter 1. A study on swarm intelligence and its various clustering algorithms in medical diagnosis -- Chapter 2. Healthcare data analytics using swarm intelligence techniques -- Chapter 3. A generic big data analytics with particleswarm optimization for clinical machine learning -- Chapter 4. A modern approach of swarm intelligence analysis in big data: methods, tools, and applications -- Chapter 5. Swarm intelligence and evolutionary machine learning algorithms forCOVID-19: pandemic and epidemic review -- Chapter 6. Swarm intelligence analysis of healthcare prediction techniques based on social media data: basics of swarm intelligence, scope of swarm intelligence, swarm intelligence in healthcare --Chapter 7. The AI-based COVID-19 personal protective equipment is smarty and secure -- Chapter 8. Internet of things-integrated remote patient monitoring system: healthcare application -- Chapter 9. An iomt and machine learning model aimedat the development of a personalized lifestyle recommendation system facilitating improved health -- Chapter 10. Securing healthcare systems integrated with IoT: fundamentals, applications, and future trends -- Chapter 11. A blockchain IoThybrid framework for security and privacy in a healthcare database network -- Chapter 12. Categorical data clustering using Meta heuristic link-based ensemble method: data clustering using soft computing techniques.
標題:	Medical informatics. -
電子資源:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-6684-6894-4
ISBN:	9781668468951 (electronic bk.)

Dynamics of swarm intelligence health analysis for the next generation
Dynamics of swarm intelligence health analysis for the next generation[electronic resource] /edited by Suresh Kumar Arumugam, Utku Kose, Sachin Sharma, Jerald Nirmal Kumar S. - Hershey, Pennsylvania :IGI Global,2023. - 1 online resource (273 p.)

Includes bibliographical references and index.

Chapter 1. A study on swarm intelligence and its various clustering algorithms in medical diagnosis -- Chapter 2. Healthcare data analytics using swarm intelligence techniques -- Chapter 3. A generic big data analytics with particleswarm optimization for clinical machine learning -- Chapter 4. A modern approach of swarm intelligence analysis in big data: methods, tools, and applications -- Chapter 5. Swarm intelligence and evolutionary machine learning algorithms forCOVID-19: pandemic and epidemic review -- Chapter 6. Swarm intelligence analysis of healthcare prediction techniques based on social media data: basics of swarm intelligence, scope of swarm intelligence, swarm intelligence in healthcare --Chapter 7. The AI-based COVID-19 personal protective equipment is smarty and secure -- Chapter 8. Internet of things-integrated remote patient monitoring system: healthcare application -- Chapter 9. An iomt and machine learning model aimedat the development of a personalized lifestyle recommendation system facilitating improved health -- Chapter 10. Securing healthcare systems integrated with IoT: fundamentals, applications, and future trends -- Chapter 11. A blockchain IoThybrid framework for security and privacy in a healthcare database network -- Chapter 12. Categorical data clustering using Meta heuristic link-based ensemble method: data clustering using soft computing techniques.

"The book discusses the role of people behavioral activity in the evolution of the traditional medical system to an intelligent system. It is based on the development of technical improvements considered in the process of intelligent systems by using cognitive techniques, swarm Intelligence deep learning, and machine learning techniques. These techniques will be used for multimodal biomedical data processing and non-invasive interpretation which efficiently improves the patient interpretation quality. Moreover, it objects to highlight the challenges of developing and proposing new ideas regarding the out-ofhospital dedicated systems directions. Solicits contributions of this book include theory, applications, and design schemes of intelligent systems, vision techniques, and biomedical applications, as well as the methodologies behind them. This book also focuses on the economic, social, and environmental impact of swarm Intelligence smarthealthcare systems. It aims to provide a detailed understanding of swarm Intelligence analysis supported applications while engaging premium smart computing methods and improved intelligent algorithms in the field of computer science. Further, the detailed assessment of IoT sensors, actuators, communication, and computing technology, and standards has been taken into considerations. Emphasis is also laid on the challenges associated with these smart healthcare systems. It includes connectivity, sensing, computation, complexity, and security issues. Therefore, this book designed for new innovations to overcome such challenges and to explore the dynamics of swarm Intelligence health analysis for the future generation. We hope to strengthen the link between the Swarm Intelligence analysis sector and mental health research in this book chapter. Various works in the digital health arena shown how real-time monitoring of mood disorders improved the overall quality of life of patients and citizens"--

ISBN: 9781668468951 (electronic bk.)Subjects--Topical Terms:

661258
Medical informatics.
Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: R859 / .D96 2023e

Dewey Class. No.: 362.10285

National Library of Medicine Call No.: W 26.55.A7 / D96 2023e

Dynamics of swarm intelligence health analysis for the next generation
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245 0 0 $a Dynamics of swarm intelligence health analysis for the next generation $h [electronic resource] / $c edited by Suresh Kumar Arumugam, Utku Kose, Sachin Sharma, Jerald Nirmal Kumar S.
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300 $a 1 online resource (273 p.)
504 $a Includes bibliographical references and index.
505 0 $a Chapter 1. A study on swarm intelligence and its various clustering algorithms in medical diagnosis -- Chapter 2. Healthcare data analytics using swarm intelligence techniques -- Chapter 3. A generic big data analytics with particleswarm optimization for clinical machine learning -- Chapter 4. A modern approach of swarm intelligence analysis in big data: methods, tools, and applications -- Chapter 5. Swarm intelligence and evolutionary machine learning algorithms forCOVID-19: pandemic and epidemic review -- Chapter 6. Swarm intelligence analysis of healthcare prediction techniques based on social media data: basics of swarm intelligence, scope of swarm intelligence, swarm intelligence in healthcare --Chapter 7. The AI-based COVID-19 personal protective equipment is smarty and secure -- Chapter 8. Internet of things-integrated remote patient monitoring system: healthcare application -- Chapter 9. An iomt and machine learning model aimedat the development of a personalized lifestyle recommendation system facilitating improved health -- Chapter 10. Securing healthcare systems integrated with IoT: fundamentals, applications, and future trends -- Chapter 11. A blockchain IoThybrid framework for security and privacy in a healthcare database network -- Chapter 12. Categorical data clustering using Meta heuristic link-based ensemble method: data clustering using soft computing techniques.
520 $a "The book discusses the role of people behavioral activity in the evolution of the traditional medical system to an intelligent system. It is based on the development of technical improvements considered in the process of intelligent systems by using cognitive techniques, swarm Intelligence deep learning, and machine learning techniques. These techniques will be used for multimodal biomedical data processing and non-invasive interpretation which efficiently improves the patient interpretation quality. Moreover, it objects to highlight the challenges of developing and proposing new ideas regarding the out-ofhospital dedicated systems directions. Solicits contributions of this book include theory, applications, and design schemes of intelligent systems, vision techniques, and biomedical applications, as well as the methodologies behind them. This book also focuses on the economic, social, and environmental impact of swarm Intelligence smarthealthcare systems. It aims to provide a detailed understanding of swarm Intelligence analysis supported applications while engaging premium smart computing methods and improved intelligent algorithms in the field of computer science. Further, the detailed assessment of IoT sensors, actuators, communication, and computing technology, and standards has been taken into considerations. Emphasis is also laid on the challenges associated with these smart healthcare systems. It includes connectivity, sensing, computation, complexity, and security issues. Therefore, this book designed for new innovations to overcome such challenges and to explore the dynamics of swarm Intelligence health analysis for the future generation. We hope to strengthen the link between the Swarm Intelligence analysis sector and mental health research in this book chapter. Various works in the digital health arena shown how real-time monitoring of mood disorders improved the overall quality of life of patients and citizens"-- $c Provided by publisher.
650 0 $a Medical informatics. $3 661258
650 0 $a Swarm intelligence. $3 577800
650 2 $a Health Information Systems. $3 3231353
650 2 $a Artificial Intelligence. $3 769149
650 2 $a Data Analysis. $3 3395925
650 2 $a Machine Learning. $3 3382522
650 2 $a Medical Informatics Computing $x trends. $3 3675532
655 4 $a Electronic books. $2 lcsh $3 542853
700 1 $a Kumar Arumugam, Suresh, $d 1979-. $3 3675528
700 1 $a Kose, Utku, $d 1985-. $3 3675529
700 1 $a Sharma, Sachin, $d 1988-. $3 3675530
700 1 $a Nirmal Kumar, S. Jerald $q (Sujeet Jerald), $d 1981-. $3 3675531
710 2 $a IGI Global. $3 1361470
856 4 0 $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-6684-6894-4