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Título
An Overview of Patient Monitoring Systems Based On Machine Learning in The Internet of Things
Autor(es)
Palabras clave
IoT
Machine learning
HealthCare
WBAN
Fecha de publicación
2024-05
Editor
CEUR Workshop Proceedings
Citación
Javid, S., & Pérez-Delgado, M. L. An Overview of Patient Monitoring Systems Based On Machine Learning in The Internet of Things. ceur-ws.org (https://ceur-ws.org/Vol-3885/paper3.pdf)
Resumen
[EN]The Internet of Things (IoT) is widely used in many applications including patient monitoring systems. The purpose of healthcare systems is to monitor the patient in order to prevent risks, deal with critical cases quickly, and establish long-distance communication for remote treatments. The IoT has a long-term impact on patient monitoring, patient management, patient physiological information, and critical care. The sensors are connected to the patient to collect the data which are first sent to system controls and then autonomously to healthcare providers. There are a variety of biosensors that send the medical information to mobile applications or websites via wireless network. Healthcare providers are thus enabled to monitor the patient and control the treatment outside of hospital walls. Therefore, the IoT medical devices require accurate patient monitoring methods in order to predict patient condition more precisely, and increase the efficiency of the network. An overview of patient monitoring systems based on machine learning in the IoT is provided in the following article.
URI
ISSN
1613-0073
Aparece en las colecciones
- CIMET. Artículos [18]
Dateien zu dieser Ressource
Nombre:
CIMET_Javid_S_PerezDelgado_ML_AnOverviewOfPatientMonitoringSystemsBasedOnML.pdfEmbargado hasta: 2099-01-01
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