2023
Chaves, A.; Montenegro, L.; Peixoto, H.; Abelha, A.; Gomes, L.; Machado, J.
Intelligent Systems in Healthcare: An Architecture Proposal Proceedings Article
Em: P., Hornos M. J. Julian Inglada V. Novais (Ed.): pp. 230-238, Springer Science and Business Media Deutschland GmbH, 2023, ISSN: 23673370, (cited By 1; Conference of 14th International Symposium on Ambient Intelligence, ISAmI 2023 ; Conference Date: 12 July 2023 Through 14 July 2023; Conference Code:301589).
Resumo | Links | BibTeX | Etiquetas: Coupling distribution; Development industry; Intelligent healthcare; Local state; Loose couplings; Microservice; Programming language researches; Proposed architectures; Reactivity state; Research and development, Decision making; Health care; Intelligent agents; Intelligent systems; Scalability, Multi agent systems
@inproceedings{Chaves2023230,
title = {Intelligent Systems in Healthcare: An Architecture Proposal},
author = {A. Chaves and L. Montenegro and H. Peixoto and A. Abelha and L. Gomes and J. Machado},
editor = {Hornos M. J. Julian Inglada V. Novais P.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174435986&doi=10.1007%2f978-3-031-43461-7_23&partnerID=40&md5=f1fab121626cc690c7357a2d9bd721ba},
doi = {10.1007/978-3-031-43461-7_23},
issn = {23673370},
year = {2023},
date = {2023-01-01},
journal = {Lecture Notes in Networks and Systems},
volume = {770 LNNS},
pages = {230-238},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {Multi-Agent Systems has existed for decades and has focused on principles such as loose coupling, distribution, reactivity, and local state. Despite substantial tool and programming language research and development, industry adoption of these systems has been restricted, particularly in the healthcare arena. Artificial intelligence, on the other hand, entails developing computer systems that can execute tasks that normally require human intelligence, such as decision-making, problem-solving, and learning. The goal of this article is to develop and implement an architecture that includes multi-agent systems with microservices, leveraging the capabilities of both methodologies in order to harness the power of Artificial Intelligence in the healthcare industry. It assesses the proposed architecture’s merits and downsides, as well as its relevance to various healthcare use cases and the influence on system scalability, adaptability, and maintainability. Indeed, the proposed architecture is capable of meeting the objectives while maintaining scalability, flexibility, and adaptability. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.},
note = {cited By 1; Conference of 14th International Symposium on Ambient Intelligence, ISAmI 2023 ; Conference Date: 12 July 2023 Through 14 July 2023; Conference Code:301589},
keywords = {Coupling distribution; Development industry; Intelligent healthcare; Local state; Loose couplings; Microservice; Programming language researches; Proposed architectures; Reactivity state; Research and development, Decision making; Health care; Intelligent agents; Intelligent systems; Scalability, Multi agent systems},
pubstate = {published},
tppubtype = {inproceedings}
}
Multi-Agent Systems has existed for decades and has focused on principles such as loose coupling, distribution, reactivity, and local state. Despite substantial tool and programming language research and development, industry adoption of these systems has been restricted, particularly in the healthcare arena. Artificial intelligence, on the other hand, entails developing computer systems that can execute tasks that normally require human intelligence, such as decision-making, problem-solving, and learning. The goal of this article is to develop and implement an architecture that includes multi-agent systems with microservices, leveraging the capabilities of both methodologies in order to harness the power of Artificial Intelligence in the healthcare industry. It assesses the proposed architecture’s merits and downsides, as well as its relevance to various healthcare use cases and the influence on system scalability, adaptability, and maintainability. Indeed, the proposed architecture is capable of meeting the objectives while maintaining scalability, flexibility, and adaptability. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.