Unraveling global malaria incidence and mortality using machine learning and artificial intelligence–driven spatial analysis
Abstract Malaria remains a significant global health concern, contributing to substantial morbidity and mortality worldwide. To inform efforts aimed at alleviating the global malaria burden, this study utilized spatial analysis, advanced machine learning (ML), and explainable AI (XAI) to identify hi...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-08-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-12872-0 |
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