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Improving prevalence estimation through data fusion: methods and validation

Autor
Aluja, T.; Daunis, J.; Brunsó, N.; Mompart, A.
Tipus d'activitat
Article en revista
Revista
BMC medical informatics and decision making
Data de publicació
2015-06-24
Volum
2015
Pàgina inicial
15
Pàgina final
49
DOI
https://doi.org/10.1186/s12911-015-0169-z Obrir en finestra nova
Repositori
http://hdl.handle.net/2117/80031 Obrir en finestra nova
URL
http://www.biomedcentral.com/1472-6947/15/49 Obrir en finestra nova
Resum
Estimation of health prevalences is usually performed with a single survey. Some attempts have been made to integrate more than one source of data. We propose here to validate this approach through data fusion. Data Fusion is the process of integrating two sources of data into one combined file. It allows us to take even greater advantage of existing information collected in databases. Here, we use data fusion to improve the estimation of health prevalences for two primary health factors: cardio...
Citació
Aluja, T., Daunis, J., Brunsó, N., Mompart, A. Improving prevalence estimation through data fusion: methods and validation. "BMC medical informatics and decision making", 24 Juny 2015, vol. 2015, p. 15-49.
Paraules clau
Cardio vascular diseases, Diabetes, Multiple imputation, Population surveys, Prevalences, Sequential regression
Grup de recerca
IMP - Information Modeling and Processing

Participants

  • Aluja Banet, Tomas  (autor)
  • Daunis Estadella, Josep  (autor)
  • Brunsó, Núria  (autor)
  • Mompart Penina, Anna  (autor)

Arxius