MARC details
| 000 -CABECERA |
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| campo de control de longitud fija |
04759nam a22003615i 4500 |
| 001 - NÚMERO DE CONTROL |
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397770 |
| 003 - IDENTIFICADOR DEL NÚMERO DE CONTROL |
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ES-MaUEC |
| 005 - FECHA Y HORA DE LA ÚLTIMA TRANSACCIÓN |
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20240104162613.0 |
| 006 - CÓDIGOS DE INFORMACIÓN DE LONGITUD FIJA--CARACTERÍSTICAS DEL MATERIAL ADICIONAL |
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a||||fo|||| 00| 0 |
| 007 - CAMPO FIJO DE DESCRIPCIÓN FÍSICA--INFORMACIÓN GENERAL |
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cr nn 008mamaa |
| 008 - DATOS DE LONGITUD FIJA--INFORMACIÓN GENERAL |
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231201s2024 sz | s |||| 0|eng d |
| 020 ## - NÚMERO INTERNACIONAL ESTÁNDAR DEL LIBRO |
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| Número Internacional Estándar del Libro |
9783031459528 |
| 024 7# - IDENTIFICADOR DE OTROS ESTÁNDARES |
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| Número estándar o código |
10.1007/978-3-031-45952-8 |
| Fuente del número o código |
doi |
| 040 ## - FUENTE DE LA CATALOGACIÓN |
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| Centro catalogador/agencia de origen |
ES-MaUEC |
| Lengua de catalogación |
spa |
| Centro/agencia transcriptor |
ES-MaUEC |
| 050 04 - SIGNATURA TOPOGRÁFICA DE LA BIBLIOTECA DEL CONGRESO |
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| Número de clasificación |
R858-859.7 |
| Número de documento/Ítem |
2024 |
| 245 00 - MENCIÓN DE TÍTULO |
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| Título |
Nature-Inspired Methods for Smart Healthcare Systems and Medical Data |
| Mención de responsabilidad, etc. |
edited by Ahmed M Anter, Mohamed Elhoseny, Anuradha D Thakare |
| 250 ## - MENCIÓN DE EDICIÓN |
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| Mención de edición |
first edition 2024 |
| 264 #1 - PRODUCCIÓN, PUBLICACIÓN, DISTRIBUCIÓN, FABRICACIÓN Y COPYRIGHT |
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| Producción, publicación, distribución, fabricación y copyright |
Cham |
| Fecha de producción, publicación, distribución, fabricación o copyright |
2024 |
| Nombre del de productor, editor, distribuidor, fabricante |
Springer International Publishing |
| 300 ## - DESCRIPCIÓN FÍSICA |
|---|
| Extensión |
1 recurso en línea |
| 336 ## - TIPO DE CONTENIDO |
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| Término de tipo de contenido |
texto |
| Código de tipo de contenido |
txt |
| Fuente |
rdacontent |
| 337 ## - TIPO DE MEDIO |
|---|
| Nombre/término del tipo de medio |
electrónico |
| Código del tipo de medio |
c |
| Fuente |
rdamedia |
| 338 ## - TIPO DE SOPORTE |
|---|
| Nombre/término del tipo de soporte |
recurso electrónico |
| Código del tipo de soporte |
cr |
| Fuente |
rdacarrier |
| 347 ## - CARACTERÍSTICAS DEL ARCHIVO DIGITAL |
|---|
| Tipo de archivo |
text file |
| Formato de codificación |
PDF |
| 505 0# - NOTA DE CONTENIDO CON FORMATO |
|---|
| Nota de contenido con formato |
Chapter. 1. A review of methods employed for forensic human identification -- Chapter. 2. AI based Medicine Intake Tracker -- Chapter. 3. Analysis of Genetic Mutations using Nature-Inspired Optimization Methods and Classification Approach -- Chapter. 4. Applications of Blockchain: A Healthcare Use Case -- Chapter. 5. Comprehensive Methodology of Contact Tracing Techniques to Reduce Pandemic Infectious Diseases Spread -- Chapter. 6. High-impact applications of IoT system-based metaheuristics -- Chapter. 7. IoT-based eHealth solutions for aging with special emphasis on aging-related inflammatory diseases: prospects and challenges -- Chapter. 8. Leveraging Meta-Heuristics in Improving Health Care Delivery: A Comprehensive Overview -- Chapter. 9. Metaheuristics algorithms for complex disease prediction -- Chapter. 10. Printed rGO-based temperature sensor for wireless body area network applications -- Chapter. 11. Recent advanced in healthcare data privacy techniques -- Chapter. 12. The ability of the CFD approach to investigate the fluid and wall hemodynamics of cerebral stenosis and aneurysm.-. |
| 520 ## - SUMARIO, ETC. |
|---|
| Sumario, etc. |
This book aims to gather high-quality research papers on developing theories, frameworks, architectures, and algorithms for solving complex challenges in smart healthcare applications for real industry use. It explores the recent theoretical and practical applications of metaheuristics and optimization in various smart healthcare contexts. The book also discusses the capability of optimization techniques to obtain optimal parameters in ML and DL technologies. It provides an open platform for academics and engineers to share their unique ideas and investigate the potential convergence of existing systems and advanced metaheuristic algorithms. The book's outcome will enable decision-makers and practitioners to select suitable optimization approaches for scheduling patients in crowded environments with minimized human errors. The healthcare system aims to improve the lives of disabled, elderly, sick individuals, and children. IoT-based systems simplify decision-making and task automation, offering an automated foundation. Nature-inspired metaheuristics and mining algorithms are crucial for healthcare applications, reducing costs, increasing efficiency, enabling accurate data analysis, and enhancing patient care. Metaheuristics improve algorithm performance and address challenges in data mining and ML, making them essential in healthcare research. Real-time IoT-based healthcare systems can be modeled using an IoT-based metaheuristic approach to generate optimal solutions. Metaheuristics are powerful technologies for optimization problems in healthcare systems. They balance exact methods, which guarantee optimal solutions but require significant computational resources, with fast but low-quality greedy methods. Metaheuristic algorithms find better solutions while minimizing computational time. The scientific community is increasingly interested in metaheuristics, incorporating techniques from AI, operations research, and soft computing. New metaheuristics offer efficient ways to address optimization problems and tackle unsolved challenges. They can be parameterized to control performance and adjust the trade-off between solution quality and resource utilization. Metaheuristics manage the trade-off between performance and solution quality, making them highly applicable to real-time applications with pragmatic objectives. |
| 988 ## - NOTA LOCAL 598 |
|---|
| Nota local 598 (boletines) |
Springer_Computer_2024 |
| 856 40 - LOCALIZACIÓN Y ACCESO ELECTRÓNICOS |
|---|
| Identificador Uniforme del Recurso |
https://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-45952-8 |
| Nota pública |
Acceso a este recurso digital (usuarios Universidad Europea de Madrid) |
| 912 ## - |
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| -- |
ZDB-2-SCS |
| 912 ## - |
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| -- |
ZDB-2-SXCS |
| 942 ## - ELEMENTOS DE PUNTO DE ACCESO ADICIONAL (KOHA) |
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| Fuente del sistema de clasificación o colocación |
Library of Congress Classification |
| Tipo de ítem Koha |
LIBRO-E NO PRÉSTAMO |