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https://hdl.handle.net/1822/89571
Título: | Architecture 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-chave: | ABI systems Adaptive Business Intelligence |
Data: | 2024 |
Editora: | Elsevier 1 |
Revista: | Procedia Computer Science |
Citação: | Gomes, 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. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/89571 |
DOI: | 10.1016/j.procs.2023.12.232 |
ISSN: | 1877-0509 |
Versão da editora: | https://www.sciencedirect.com/science/article/pii/S1877050923022445 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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1-s2.0-S1877050923022445-main.pdf | 522,33 kB | Adobe PDF | Ver/Abrir |
Este trabalho está licenciado sob uma Licença Creative Commons