TY  - JOUR
AU  - Medina Quero, Javier
AU  - Lopez Medina, Miguel Angel
AU  - Salguero Hidalgo, Alberto
AU  - Espinilla, Macarena
PY  - 2018
DO  - 10.1109/ACCESS.2018.2828652
SN  - 2169-3536
UR  - http://hdl.handle.net/10668/18966
T2  - Ieee access
AB  - Predicting the urgency demand of patients at health centers in smart cities supposes a challenge for adapting emergency service in advance. In this paper, we propose a methodology to predict the number of cases of chronic obstructive pulmonary disease...
LA  - en
PB  - Ieee-inst electrical electronics engineers inc
KW  - Predicting urgency demand
KW  - long short-term memory
KW  - temporal aggregation
KW  - fuzzy linguistic approach
KW  - Obstructive pulmonary-disease
KW  - Linguistic term sets
KW  - Hospital admissions
KW  - City
KW  - Pollen
TI  - Predicting the Urgency Demand of COPD Patients From Environmental Sensors Within Smart Cities With High-Environmental Sensitivity
TY  - research article
VL  - 6
ER  -