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algorithm e » algorithm _ (Expand Search), algorithm b (Expand Search), algorithm a (Expand Search)
e learning » _ learning (Expand Search), deep learning (Expand Search)
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Spatial locations of reported FMD outbreaks
Published 2025“…Centered on known outbreak information, we predicted high-risk areas using similar regional ecological features. Using a multi-algorithm machine-learning ensemble that includes random forest, support vector, and gradient boosting, 15 predictive variables (i.e livestock densities, land cover, and climate), 660 FMD outbreaks from 13 years (2009-2022) in the region including the outbreaks from India, Bangladesh, and Sri Lanka we identified that Sri Lanka and Bangladesh appeared to have low to medium outbreak risk in the range of 0.04 to 0.55. …”
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Random Forest feature importance plot.
Published 2025“…Centered on known outbreak information, we predicted high-risk areas using similar regional ecological features. Using a multi-algorithm machine-learning ensemble that includes random forest, support vector, and gradient boosting, 15 predictive variables (i.e., livestock densities, land cover, and climate), 660 FMD outbreaks from 13 years (2009–2022) in the region including the outbreaks from India, Bangladesh, and Sri Lanka we identified that Sri Lanka and Bangladesh appeared to have low to medium outbreak risk in the range of 0.04 to 0.55. …”
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