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Dynamic Models Supporting Personalised Chronic Disease Management through Healthcare Sensors with Interactive Process Mining

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Dynamic Models Supporting Personalised Chronic Disease Management through Healthcare Sensors with Interactive Process Mining

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Valero Ramon, Z.; Fernández Llatas, C.; Valdivieso, B.; Traver Salcedo, V. (2020). Dynamic Models Supporting Personalised Chronic Disease Management through Healthcare Sensors with Interactive Process Mining. Sensors. 20(18):1-25. https://doi.org/10.3390/s20185330

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/166838

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Title: Dynamic Models Supporting Personalised Chronic Disease Management through Healthcare Sensors with Interactive Process Mining
Author: Valero Ramon, Zoe Fernández Llatas, Carlos Valdivieso, Bernardo Traver Salcedo, Vicente
UPV Unit: Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica
Issued date:
Abstract:
[EN] Rich streams of continuous data are available through Smart Sensors representing a unique opportunity to develop and analyse risk models in healthcare and extract knowledge from data. There is a niche for developing ...[+]
Subjects: Process mining , Interactive , Dynamic models , Chronic diseases , Obesity , Hypertension , Hyperglycemia , Smart sensors
Copyrigths: Reconocimiento (by)
Source:
Sensors. (eissn: 1424-8220 )
DOI: 10.3390/s20185330
Publisher:
MDPI AG
Publisher version: https://doi.org/10.3390/s20185330
Project ID:
info:eu-repo/grantAgreement/EC/H2020/727560/EU/Collective wisdom driving public health policies/
Thanks:
This research was partially funded by the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement no. 727560.
Type: Artículo

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