Quantitative Forecasting of Malaria Parasite Using Machine Learning Models: MLR, ANN, ANFIS and Random Forest

Quantitative Forecasting of Malaria Parasite Using Machine Learning Models: MLR, ANN, ANFIS and Random Forest

Malaria continues to be a major barrier to socioeconomic development in Africa, where its death rate is over 90%. The predictive power of many machine learning models—such as multi-linear regression (MLR), artificial neural networks (ANN), adaptive neuro-fuzzy inference systems (ANFISs) and Random F...

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Bibliographic Details
Main Authors: Dilber Uzun Ozsahin, Basil Barth Duwa, Ilker Ozsahin, Berna Uzun
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Diagnostics
Subjects:
adaptive neuro-fuzzy inference system (ANFIS)
artificial neural network (ANN)
statistical prediction
malaria parasite
machine learning models
multiple linear regression (MLR)
Online Access:https://www.mdpi.com/2075-4418/14/4/385

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https://www.mdpi.com/2075-4418/14/4/385

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