Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/89571

TítuloArchitecture proposal for deploying and integrating intelligent models in ABI
Autor(es)Gomes, Rui
Duarte, Júlio Miguel Marques
Quintas, Cesar
Salazar, Maria Manuel
Santos, Manuel
Palavras-chaveABI systems
Adaptive Business Intelligence
Data2024
EditoraElsevier 1
RevistaProcedia Computer Science
CitaçãoGomes, R., Duarte, J., Quintas, C., Salazar, M. M., & Santos, M. F. (2024). Architecture proposal for deploying and integrating intelligent models in ABI. Procedia Computer Science. Elsevier BV. http://doi.org/10.1016/j.procs.2023.12.232
Resumo(s)The integration of Adaptive Business Intelligence systems in healthcare has garnered significant attention due to their potential to manage the ever-growing volume of healthcare data and enhance the quality of care provided to society. ABI systems also play a crucial role in supporting hospital administrators in making strategic decisions. To facilitate the transparency and interoperability of these solutions, the scientific community has embarked on various studies to develop technologic architectures capable of meeting the complex requirements of healthcare settings. One of the key challenges in adopting this technology is the creation and integration of prediction and optimization models in an automated and semi-autonomous manner. This article presents a novel and robust microservices architecture designed to streamline the deployment of intelligent models and seamlessly integrate them within the ABI system. This paper begins by introducing the problem of deploying and integrating intelligent models into ABI systems, providing essential context on ABI systems within the healthcare domain. Subsequently, it details the proposed architecture, outlining its technical approaches and highlighting the advantages it brings to the healthcare ecosystem. Finally, the paper concludes by summarizing the contributions and future directions for research in this critical area, emphasizing the potential impact of this architecture on improving healthcare intelligence systems.
TipoArtigo em ata de conferência
URIhttps://hdl.handle.net/1822/89571
DOI10.1016/j.procs.2023.12.232
ISSN1877-0509
Versão da editorahttps://www.sciencedirect.com/science/article/pii/S1877050923022445
Arbitragem científicayes
AcessoAcesso aberto
Aparece nas coleções:CAlg - Artigos em livros de atas/Papers in proceedings

Ficheiros deste registo:
Ficheiro Descrição TamanhoFormato 
1-s2.0-S1877050923022445-main.pdf522,33 kBAdobe PDFVer/Abrir

Este trabalho está licenciado sob uma Licença Creative Commons Creative Commons

Partilhe no FacebookPartilhe no TwitterPartilhe no DeliciousPartilhe no LinkedInPartilhe no DiggAdicionar ao Google BookmarksPartilhe no MySpacePartilhe no Orkut
Exporte no formato BibTex mendeley Exporte no formato Endnote Adicione ao seu ORCID