Spatiotemporal models of dengue epidemiology in the Philippines: Integrating remote sensing and interpretable machine learning

Author:

Buebos-Esteve Don EnricoORCID,Dagamac Nikki Heherson A.

Publisher

Elsevier BV

Reference99 articles.

1. Is the changing rainfall patterns of Kano State and its adverse impacts an indication of climate change?;Abaje;Eur. Sci. J.,2014

2. Trends in dengue research in the Philippines: a systematic review;Agrupis;PLoS Negl. Trop. Dis.,2019

3. Interpretable machine learning in healthcare;Ahmad,2018

4. Visualizing the effects of predictor variables in black box supervised learning models;Apley;J. R. Stat. Soc. Ser. B Stat. Methodol.,2020

5. A Multi-Stage Machine learning approach to predict dengue incidence: a case study in Mexico;Appice;IEEe Access,2020

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