FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3088943773> ?p ?o ?g. }

• W3088943773 endingPage "e0008056" @default.
• W3088943773 startingPage "e0008056" @default.
• W3088943773 abstract "The robust estimate and forecast capability of random forests (RF) has been widely recognized, however this ensemble machine learning method has not been widely used in mosquito-borne disease forecasting. In this study, two sets of RF models were developed at the national (pooled department-level data) and department level in Colombia to predict weekly dengue cases for 12-weeks ahead. A pooled national model based on artificial neural networks (ANN) was also developed and used as a comparator to the RF models. The various predictors included historic dengue cases, satellite-derived estimates for vegetation, precipitation, and air temperature, as well as population counts, income inequality, and education. Our RF model trained on the pooled national data was more accurate for department-specific weekly dengue cases estimation compared to a local model trained only on the department's data. Additionally, the forecast errors of the national RF model were smaller to those of the national pooled ANN model and were increased with the forecast horizon increasing from one-week-ahead (mean absolute error, MAE: 9.32) to 12-weeks ahead (MAE: 24.56). There was considerable variation in the relative importance of predictors dependent on forecast horizon. The environmental and meteorological predictors were relatively important for short-term dengue forecast horizons while socio-demographic predictors were relevant for longer-term forecast horizons. This study demonstrates the potential of RF in dengue forecasting with a feasible approach of using a national pooled model to forecast at finer spatial scales. Furthermore, including sociodemographic predictors is likely to be helpful in capturing longer-term dengue trends." @default.
• W3088943773 created "2020-10-01" @default.
• W3088943773 creator A5014872992 @default.
• W3088943773 creator A5029486851 @default.
• W3088943773 creator A5033497551 @default.
• W3088943773 creator A5034438342 @default.
• W3088943773 creator A5049058088 @default.
• W3088943773 creator A5057907135 @default.
• W3088943773 creator A5072528874 @default.
• W3088943773 creator A5073187748 @default.
• W3088943773 creator A5087787202 @default.
• W3088943773 creator A5091372470 @default.
• W3088943773 date "2020-09-24" @default.
• W3088943773 modified "2023-10-14" @default.
• W3088943773 title "Machine learning and dengue forecasting: Comparing random forests and artificial neural networks for predicting dengue burden at national and sub-national scales in Colombia" @default.
• W3088943773 cites W1577378836 @default.
• W3088943773 cites W1964473461 @default.
• W3088943773 cites W1972431236 @default.
• W3088943773 cites W1978231049 @default.
• W3088943773 cites W1983865151 @default.
• W3088943773 cites W1984069615 @default.
• W3088943773 cites W1987199596 @default.
• W3088943773 cites W1987805055 @default.
• W3088943773 cites W1997994299 @default.
• W3088943773 cites W2006787114 @default.
• W3088943773 cites W2016589492 @default.
• W3088943773 cites W2026004405 @default.
• W3088943773 cites W2027712265 @default.
• W3088943773 cites W2028079124 @default.
• W3088943773 cites W2031462067 @default.
• W3088943773 cites W2046313806 @default.
• W3088943773 cites W2049229003 @default.
• W3088943773 cites W2056298081 @default.
• W3088943773 cites W2079515288 @default.
• W3088943773 cites W2079766880 @default.
• W3088943773 cites W2084341220 @default.
• W3088943773 cites W2101277061 @default.
• W3088943773 cites W2101394945 @default.
• W3088943773 cites W2103958165 @default.
• W3088943773 cites W2116512828 @default.
• W3088943773 cites W2118023920 @default.
• W3088943773 cites W2131222241 @default.
• W3088943773 cites W2131822674 @default.
• W3088943773 cites W2138034780 @default.
• W3088943773 cites W2151169884 @default.
• W3088943773 cites W2164643570 @default.
• W3088943773 cites W2168876014 @default.
• W3088943773 cites W2187558081 @default.
• W3088943773 cites W2252436850 @default.
• W3088943773 cites W2307051252 @default.
• W3088943773 cites W2321003535 @default.
• W3088943773 cites W2324659721 @default.
• W3088943773 cites W2331700789 @default.
• W3088943773 cites W2338936985 @default.
• W3088943773 cites W2471292289 @default.
• W3088943773 cites W2473922097 @default.
• W3088943773 cites W2514541415 @default.
• W3088943773 cites W2525587339 @default.
• W3088943773 cites W2530703975 @default.
• W3088943773 cites W2588108191 @default.
• W3088943773 cites W2590890587 @default.
• W3088943773 cites W2604870469 @default.
• W3088943773 cites W2766013390 @default.
• W3088943773 cites W2781898996 @default.
• W3088943773 cites W2783825033 @default.
• W3088943773 cites W2791894277 @default.
• W3088943773 cites W2800543972 @default.
• W3088943773 cites W2801896044 @default.
• W3088943773 cites W2801974413 @default.
• W3088943773 cites W2808945087 @default.
• W3088943773 cites W2887889066 @default.
• W3088943773 cites W2888798488 @default.
• W3088943773 cites W2889514903 @default.
• W3088943773 cites W2899711729 @default.
• W3088943773 cites W2911964244 @default.
• W3088943773 cites W2953342850 @default.
• W3088943773 cites W2977229943 @default.
• W3088943773 cites W3034099090 @default.
• W3088943773 cites W4210318339 @default.
• W3088943773 cites W4230453131 @default.
• W3088943773 cites W2783163105 @default.
• W3088943773 doi "https://doi.org/10.1371/journal.pntd.0008056" @default.
• W3088943773 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7537891" @default.
• W3088943773 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/32970674" @default.
• W3088943773 hasPublicationYear "2020" @default.
• W3088943773 type Work @default.
• W3088943773 sameAs 3088943773 @default.
• W3088943773 citedByCount "32" @default.
• W3088943773 countsByYear W30889437732021 @default.
• W3088943773 countsByYear W30889437732022 @default.
• W3088943773 countsByYear W30889437732023 @default.
• W3088943773 crossrefType "journal-article" @default.
• W3088943773 hasAuthorship W3088943773A5014872992 @default.
• W3088943773 hasAuthorship W3088943773A5029486851 @default.
• W3088943773 hasAuthorship W3088943773A5033497551 @default.
• W3088943773 hasAuthorship W3088943773A5034438342 @default.
• W3088943773 hasAuthorship W3088943773A5049058088 @default.
• W3088943773 hasAuthorship W3088943773A5057907135 @default.

• next