Abstract
The need to perform accurate and timely diagnoses in cases involving patients in a post-operative situation is one of the challenges involved in the area of health care. According to studies in some countries, patients are concerned about spending more time in the hospital after surgery. In this sense, we tried to verify how the implementation of solutions that use IT devices and techniques could improve this process of diagnosis. Considering those, this article proposes a multi-agent system architecture that uses, among other techniques, IoT devices, machine learning algorithms and the XMPP protocol with the purpose of determining the best referral to post-operative patients based on medical information. The results obtained showed an accuracy of almost 90% in the evaluated cases, evidencing the possibility of the use and evolution of the IT solution that was developed.
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- 1.
Available at: https://github.com/afonsoblneto/eHealth.
- 2.
Available at: https://github.com/afonsoblneto/post_operative_ml.
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Loureiro, T.C.J., Neto, A.B.L., Rocha, F.A.A., Aguiar, F.A.R., Fernandez, M.P. (2020). Multi-Agent System and Classification Algorithms Applied for eHealth in Order to Support the Referral of Post-operative Patients. In: Novais, P., Lloret, J., Chamoso, P., Carneiro, D., Navarro, E., Omatu, S. (eds) Ambient Intelligence – Software and Applications –,10th International Symposium on Ambient Intelligence. ISAmI 2019. Advances in Intelligent Systems and Computing, vol 1006 . Springer, Cham. https://doi.org/10.1007/978-3-030-24097-4_2
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