A supervised machine learning approach for diagnosing Lassa fever and viral Hemorrhagic fever types reliant on observed signs
Solomon O. Alile Department of Computer Science, Faculty of Physical Sciences, University of Benin, Benin City, Nigeria DOI: https://doi.org/10.14456/apst.2022.65 Keywords: Lassa fever Viral hemorrhagic fevers Prediction Supervised machine Learning Bayesian belief network Abstract Lassa hemorrhagic fever is an infectious life-threatening fever characterized by bleeding caused by the single-stranded virus of the Arenaviridae virus family transmitted […]