Matches in SemOpenAlex for { <https://semopenalex.org/work/W4200438504> ?p ?o ?g. }
- W4200438504 endingPage "106296" @default.
- W4200438504 startingPage "106296" @default.
- W4200438504 abstract "This study compares two adaptive neuro-fuzzy inference system (ANFIS) and principal component analysis (PCA)-ANFIS techniques for spatial modeling and forecasting of zoonotic cutaneous leishmaniasis (ZCL) cases in rural districts of Golestan province, Iran. We collected and prepared data on ZCL cases and climatic, topographic, vegetation, and human population factors. By applying the PCA algorithm, the parameters affecting the ZCL incidence were decomposed into principal components (PCs), and their dimensions were reduced. Then, PCs were used to train the ANFIS model. To evaluate the proposed approaches in model assessment phase, we used test data in 2016. In this phase, we showed that PCA-ANFIS model with values of R2 = 0.791, MAE = 0.681, RMSE = 0.904 compared to ANFIS model with values of R2 = 0.705, MAE = 0.827, RMSE = 1.073 has better performance in prediction of the ZCL cases. Actual and predicted maps of ZCL cases in 2016 by both models demonstrated that the high-risk regions of the disease are located in the northeastern, northern parts, and some central rural districts of Golestan province. Sensitivity analysis of the ANFIS model showed that population, vegetation, average wind speed, elevation, and average soil temperature, respectively, are the most significant factors in predicting the ZCL cases. The findings indicated the importance of machine learning (ML) techniques (ANFIS and PCA-ANFIS) in medical geography studies. By using these approaches, with less cost and shorter time, high-risk areas of diseases can be predicted, and the most effective factors on the spatial prediction of diseases can be identified. Public health policymakers can use these useful tools to control and prevent the disease and to allocate resources to disease-prone areas." @default.
- W4200438504 created "2021-12-31" @default.
- W4200438504 creator A5014417974 @default.
- W4200438504 creator A5036605286 @default.
- W4200438504 creator A5047762196 @default.
- W4200438504 date "2022-04-01" @default.
- W4200438504 modified "2023-10-18" @default.
- W4200438504 title "Spatial modeling of zoonotic cutaneous leishmaniasis with regard to potential environmental factors using ANFIS and PCA-ANFIS methods" @default.
- W4200438504 cites W1995995344 @default.
- W4200438504 cites W1997320786 @default.
- W4200438504 cites W2005413963 @default.
- W4200438504 cites W2019207321 @default.
- W4200438504 cites W2031722061 @default.
- W4200438504 cites W2064319214 @default.
- W4200438504 cites W2094954761 @default.
- W4200438504 cites W2107824224 @default.
- W4200438504 cites W2124365263 @default.
- W4200438504 cites W2133321814 @default.
- W4200438504 cites W2155955992 @default.
- W4200438504 cites W2160971502 @default.
- W4200438504 cites W2164303307 @default.
- W4200438504 cites W2294798173 @default.
- W4200438504 cites W2406496922 @default.
- W4200438504 cites W2507534465 @default.
- W4200438504 cites W2565001539 @default.
- W4200438504 cites W2597648394 @default.
- W4200438504 cites W2599046151 @default.
- W4200438504 cites W2614461932 @default.
- W4200438504 cites W2621028994 @default.
- W4200438504 cites W2734879551 @default.
- W4200438504 cites W2755867263 @default.
- W4200438504 cites W2758580191 @default.
- W4200438504 cites W2777136302 @default.
- W4200438504 cites W2790347566 @default.
- W4200438504 cites W2809228517 @default.
- W4200438504 cites W2887695198 @default.
- W4200438504 cites W2888231268 @default.
- W4200438504 cites W2890029039 @default.
- W4200438504 cites W2890599451 @default.
- W4200438504 cites W2908603159 @default.
- W4200438504 cites W2911416364 @default.
- W4200438504 cites W2940519565 @default.
- W4200438504 cites W2985526038 @default.
- W4200438504 cites W2997783955 @default.
- W4200438504 cites W3080548462 @default.
- W4200438504 cites W3102866270 @default.
- W4200438504 cites W3161802366 @default.
- W4200438504 doi "https://doi.org/10.1016/j.actatropica.2021.106296" @default.
- W4200438504 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/34958766" @default.
- W4200438504 hasPublicationYear "2022" @default.
- W4200438504 type Work @default.
- W4200438504 citedByCount "4" @default.
- W4200438504 countsByYear W42004385042022 @default.
- W4200438504 countsByYear W42004385042023 @default.
- W4200438504 crossrefType "journal-article" @default.
- W4200438504 hasAuthorship W4200438504A5014417974 @default.
- W4200438504 hasAuthorship W4200438504A5036605286 @default.
- W4200438504 hasAuthorship W4200438504A5047762196 @default.
- W4200438504 hasConcept C105795698 @default.
- W4200438504 hasConcept C154945302 @default.
- W4200438504 hasConcept C186108316 @default.
- W4200438504 hasConcept C195975749 @default.
- W4200438504 hasConcept C205649164 @default.
- W4200438504 hasConcept C27438332 @default.
- W4200438504 hasConcept C2908647359 @default.
- W4200438504 hasConcept C33923547 @default.
- W4200438504 hasConcept C39432304 @default.
- W4200438504 hasConcept C41008148 @default.
- W4200438504 hasConcept C58166 @default.
- W4200438504 hasConcept C58640448 @default.
- W4200438504 hasConcept C71924100 @default.
- W4200438504 hasConcept C99454951 @default.
- W4200438504 hasConceptScore W4200438504C105795698 @default.
- W4200438504 hasConceptScore W4200438504C154945302 @default.
- W4200438504 hasConceptScore W4200438504C186108316 @default.
- W4200438504 hasConceptScore W4200438504C195975749 @default.
- W4200438504 hasConceptScore W4200438504C205649164 @default.
- W4200438504 hasConceptScore W4200438504C27438332 @default.
- W4200438504 hasConceptScore W4200438504C2908647359 @default.
- W4200438504 hasConceptScore W4200438504C33923547 @default.
- W4200438504 hasConceptScore W4200438504C39432304 @default.
- W4200438504 hasConceptScore W4200438504C41008148 @default.
- W4200438504 hasConceptScore W4200438504C58166 @default.
- W4200438504 hasConceptScore W4200438504C58640448 @default.
- W4200438504 hasConceptScore W4200438504C71924100 @default.
- W4200438504 hasConceptScore W4200438504C99454951 @default.
- W4200438504 hasLocation W42004385041 @default.
- W4200438504 hasLocation W42004385042 @default.
- W4200438504 hasOpenAccess W4200438504 @default.
- W4200438504 hasPrimaryLocation W42004385041 @default.
- W4200438504 hasRelatedWork W1975584913 @default.
- W4200438504 hasRelatedWork W2078576161 @default.
- W4200438504 hasRelatedWork W2119158312 @default.
- W4200438504 hasRelatedWork W2158774094 @default.
- W4200438504 hasRelatedWork W2317975685 @default.
- W4200438504 hasRelatedWork W2359456886 @default.
- W4200438504 hasRelatedWork W2361219484 @default.
- W4200438504 hasRelatedWork W2484383958 @default.