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Three-Month Real-Time Dengue Forecast Models: An Early Warning System for Outbreak Alerts and Policy Decision Support in Singapore.
Shi Y, Liu X, Kok SY, Rajarethinam J, Liang S, Yap G, Chong CS, Lee KS, Tan SS, Chin CK, Lo A, Kong W, Ng LC, Cook AR. Shi Y, et al. Among authors: yap g. Environ Health Perspect. 2016 Sep;124(9):1369-75. doi: 10.1289/ehp.1509981. Epub 2015 Dec 11. Environ Health Perspect. 2016. PMID: 26662617 Free PMC article.
CONCLUSIONS: Statistical models built using machine learning methods such as LASSO have the potential to markedly improve forecasting techniques for recurrent infectious disease outbreaks such as dengue. CITATION: Shi Y, Liu X, Kok SY, Rajarethinam J, Liang S, Yap G …
CONCLUSIONS: Statistical models built using machine learning methods such as LASSO have the potential to markedly improve forecasting techni …
Mapping dengue risk in Singapore using Random Forest.
Ong J, Liu X, Rajarethinam J, Kok SY, Liang S, Tang CS, Cook AR, Ng LC, Yap G. Ong J, et al. Among authors: yap g. PLoS Negl Trop Dis. 2018 Jun 18;12(6):e0006587. doi: 10.1371/journal.pntd.0006587. eCollection 2018 Jun. PLoS Negl Trop Dis. 2018. PMID: 29912940 Free PMC article.
Spatio-temporal analysis of the main dengue vector populations in Singapore.
Sun H, Dickens BL, Richards D, Ong J, Rajarethinam J, Hassim MEE, Lim JT, Carrasco LR, Aik J, Yap G, Cook AR, Ng LC. Sun H, et al. Among authors: yap g. Parasit Vectors. 2021 Jan 11;14(1):41. doi: 10.1186/s13071-020-04554-9. Parasit Vectors. 2021. PMID: 33430945 Free PMC article.
432 results