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Published on in Vol 6, No 1 (2014):

JMIR Publications logo: Advancing Digital Health & Open Science

Predicting Malaria in a Highly Endemic Country using Environmental and Clinical Data Sources

Predicting Malaria in a Highly Endemic Country using Environmental and Clinical Data Sources

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Journals

  1. Ezenwa N, Latorre-Carmona P, Sánchez J. Machine learning models to predict the risk of malaria outbreaks using balanced climatic and non-climatic data. Asian Pacific Journal of Tropical Medicine 2026;19(3):129 View

Books/Policy Documents

  1. Adamu Y, Singh J. Proceedings of Fourth International Conference on Computing, Communications, and Cyber-Security. View

Conference Proceedings

  1. Muhammad B, Varol A. 2021 9th International Symposium on Digital Forensics and Security (ISDFS). A Symptom-Based Machine Learning Model for Malaria Diagnosis in Nigeria View