Dynamics of swarm intelligence health analysis for the next generation:
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 lear...
Gespeichert in:
| Weitere Verfasser: | , , , |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hershey PA, USA
IGI Global
[2023]
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| Schriftenreihe: | Advances in healthcare information systems and administration (AHISA)
|
| Schlagworte: | |
| Online-Zugang: | DE-91 DE-706 DE-83 DE-898 DE-1050 Volltext |
| Zusammenfassung: | 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 smart healthcare 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 |
| Beschreibung: | 1 Online-Ressource (xvi, 273 Seiten) Illustrationen, Diagramme |
| ISBN: | 9781668468951 |
| DOI: | 10.4018/978-1-6684-6894-4 |
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| 245 | 1 | 0 | |a Dynamics of swarm intelligence health analysis for the next generation |c Arumugam Suresh Kumar (Jain University (Deemed), India), Utku Kose (Suleyman Demirel University, Turkey), Sachin Sharma (Graphic Era University (Deemed), India), S. Jerald Nirmal Kumar (Sharda University, India) |
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| 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 smart healthcare 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 | ||
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Datensatz im Suchindex
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| index_date | 2024-07-03T22:26:42Z |
| indexdate | 2024-12-17T19:01:34Z |
| institution | BVB |
| isbn | 9781668468951 |
| language | English |
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| spelling | Dynamics of swarm intelligence health analysis for the next generation Arumugam Suresh Kumar (Jain University (Deemed), India), Utku Kose (Suleyman Demirel University, Turkey), Sachin Sharma (Graphic Era University (Deemed), India), S. Jerald Nirmal Kumar (Sharda University, India) Hershey PA, USA IGI Global [2023] 1 Online-Ressource (xvi, 273 Seiten) Illustrationen, Diagramme txt rdacontent c rdamedia cr rdacarrier Advances in healthcare information systems and administration (AHISA) 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 smart healthcare 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 Medical informatics Swarm intelligence Suresh Kumar, Arumugam 1979- edt Köse, Utku 1985- (DE-588)1189595796 edt Sharma, Sachin 1988- edt Nirmal Kumar, S. Jerald 1981- edt Erscheint auch als Druck-Ausgabe 1668468948 Erscheint auch als Druck-Ausgabe 9781668468944 https://doi.org/10.4018/978-1-6684-6894-4 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Dynamics of swarm intelligence health analysis for the next generation Medical informatics Swarm intelligence |
| title | Dynamics of swarm intelligence health analysis for the next generation |
| title_auth | Dynamics of swarm intelligence health analysis for the next generation |
| title_exact_search | Dynamics of swarm intelligence health analysis for the next generation |
| title_exact_search_txtP | Dynamics of swarm intelligence health analysis for the next generation |
| title_full | Dynamics of swarm intelligence health analysis for the next generation Arumugam Suresh Kumar (Jain University (Deemed), India), Utku Kose (Suleyman Demirel University, Turkey), Sachin Sharma (Graphic Era University (Deemed), India), S. Jerald Nirmal Kumar (Sharda University, India) |
| title_fullStr | Dynamics of swarm intelligence health analysis for the next generation Arumugam Suresh Kumar (Jain University (Deemed), India), Utku Kose (Suleyman Demirel University, Turkey), Sachin Sharma (Graphic Era University (Deemed), India), S. Jerald Nirmal Kumar (Sharda University, India) |
| title_full_unstemmed | Dynamics of swarm intelligence health analysis for the next generation Arumugam Suresh Kumar (Jain University (Deemed), India), Utku Kose (Suleyman Demirel University, Turkey), Sachin Sharma (Graphic Era University (Deemed), India), S. Jerald Nirmal Kumar (Sharda University, India) |
| title_short | Dynamics of swarm intelligence health analysis for the next generation |
| title_sort | dynamics of swarm intelligence health analysis for the next generation |
| topic | Medical informatics Swarm intelligence |
| topic_facet | Medical informatics Swarm intelligence |
| url | https://doi.org/10.4018/978-1-6684-6894-4 |
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