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Oblique decision trees for spatial pattern detection: optimal algorithm and application to malaria risk

Jean Gaudart*, Belco Poudiougou, Stéphane Ranque and Ogobara Doumbo

BMC Medical Research Methodology 2005, 5:22 doi:10.1186/1471-2288-5-22

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Stratification of the severity of critically ill patients with classification trees

Javier Trujillano, Mariona Badia, Luis Serviá, Jaume March, Angel Rodriguez-Pozo BMC Medical Research Methodology 2009, 9:83 (9 December 2009)

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Using the SaTScan method to detect local malaria clusters for guiding malaria control programmes

Marlize Coleman, Michael Coleman, Aaron M Mabuza, Gerdalize Kok, Maureen Coetzee, David N Durrheim Malaria Journal 2009, 8:68 (17 April 2009)

Abstract | Full text | PDF | PubMed |  Editor’s summary

Understanding the clustering of malaria cases is important for targeting control efforts at local levels, especially in areas of low malaria transmission.

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Malaria in central Vietnam: analysis of risk factors by multivariate analysis and classification tree models

Ngo Thang, Annette Erhart, Niko Speybroeck, Le Hung, Le Thuan, Cong Hung, Pham Ky, Marc Coosemans, Umberto D'Alessandro Malaria Journal 2008, 7:28 (30 January 2008)

Abstract | Full text | PDF | PubMed | Cited on BioMed Central |  Editor’s summary

A combination of two complementary statistical approaches (logistic regression and CART) to classify the malaria risk factors

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