2023
Sousa, R.; Peixoto, H.; Abelha, A.; Machado, J.
Implementing a Software-as-a-Service Strategy in Healthcare Workflows Proceedings Article
Em: S., Analide C. Sitek P. Ossowski (Ed.): pp. 347-356, Springer Science and Business Media Deutschland GmbH, 2023, ISSN: 23673370, (cited By 0; Conference of 20th International Symposium on Distributed Computing and Artificial Intelligence, DCAI 2023 ; Conference Date: 12 July 2023 Through 14 July 2023; Conference Code:298499).
Resumo | Links | BibTeX | Etiquetas: Big data; Cost effectiveness; Diagnosis; Health care; Information management; Real time systems; Software agents; Software as a service (SaaS); Software testing; Web services, Case-studies; Cloud paradigm; Healthcare facility; Healthcare technology; Healthcare workflow; Laboratory test; Large amounts of data; Real-time information systems; Service strategy; Software-as-a- Service (SaaS), Multi agent systems
@inproceedings{Sousa2023347,
title = {Implementing a Software-as-a-Service Strategy in Healthcare Workflows},
author = {R. Sousa and H. Peixoto and A. Abelha and J. Machado},
editor = {Analide C. Sitek P. Ossowski S.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172215447&doi=10.1007%2f978-3-031-38333-5_35&partnerID=40&md5=65351fd6a4cb540be0182fe1e9567940},
doi = {10.1007/978-3-031-38333-5_35},
issn = {23673370},
year = {2023},
date = {2023-01-01},
journal = {Lecture Notes in Networks and Systems},
volume = {740 LNNS},
pages = {347-356},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {The spread of healthcare technology has resulted in a massive amount of data, particularly in the form of laboratory test results, which play an important role in medical diagnosis and treatment. However, managing and interpreting such large amounts of data has proven increasingly difficult, particularly for resource-constrained healthcare facilities. To address this issue, we present a multi-agent system for effective laboratory test result management based on Software-as-a-Service (SaaS) technology. This paper contains a case study that evaluates the system’s performance and efficacy. The study’s goal is to examine the viability of using a multi-agent system and SaaS technology to manage laboratory test data, highlighting the system’s advantages over conventional alternatives. In the age of big data, the deployment of this system could dramatically improve healthcare service efficiency, quality, and cost-effectiveness. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.},
note = {cited By 0; Conference of 20th International Symposium on Distributed Computing and Artificial Intelligence, DCAI 2023 ; Conference Date: 12 July 2023 Through 14 July 2023; Conference Code:298499},
keywords = {Big data; Cost effectiveness; Diagnosis; Health care; Information management; Real time systems; Software agents; Software as a service (SaaS); Software testing; Web services, Case-studies; Cloud paradigm; Healthcare facility; Healthcare technology; Healthcare workflow; Laboratory test; Large amounts of data; Real-time information systems; Service strategy; Software-as-a- Service (SaaS), Multi agent systems},
pubstate = {published},
tppubtype = {inproceedings}
}