Systematic review on the application of machine learning to quantitative structure–activity relationship modeling against Plasmodium falciparum

OE Oguike, CH Ugwuishiwu, CN Asogwa, CO Nnadi… - Molecular Diversity, 2022 - Springer
Malaria accounts for over two million deaths globally. To flatten this curve, there is a need to
develop new and high potent drugs against Plasmodium falciparum. Some major …

Predicting malaria outbreak in The Gambia using machine learning techniques

O Khan, JO Ajadi, MP Hossain - Plos one, 2024 - journals.plos.org
Malaria is the most common cause of death among the parasitic diseases. Malaria continues
to pose a growing threat to the public health and economic growth of nations in the tropical …

On the goodness of fit of parametric and non-parametric data mining techniques: the case of malaria incidence thresholds in Uganda

FF Bbosa, J Nabukenya, P Nabende… - Health and Technology, 2021 - Springer
To identify which data mining technique (parametric or non-parametric) best fits the
predictions on imbalanced malaria incidence dataset. The researchers compared …

Malaria outbreak detection with machine learning methods

G Comert, N Begashaw, A Turhan-Comert - BioRxiv, 2020 - biorxiv.org
In this paper, we utilized and compared selected machine learning techniques to detect
malaria out-break using observed variables of maximum temperature, minimum …

A framework for predicting malaria using naïve Bayes classifier

A Aliyu, R Prasad, M Fonkam - International Journal of …, 2018 - inderscienceonline.com
Malaria, a life-threatening parasite contained in the spittle of mosquitoes, and is transmitted
via a bite. This study designs a framework for predicting malaria using a probabilistic …

Machine learning analysis and agent-based modelling of malaria transmission

B Modu, N Polovina, Y Lan… - Fuzzy Systems and Data …, 2018 - ebooks.iospress.nl
Malaria is the leading cause of death in many countries. Numerous studies have been
carried out to introduce prevention mechanisms; but most methods employed are limited to …

[PDF][PDF] Malaria Disease Prediction and Grading System: A Performance Model of Multinomial Naïve Bayes (MNB) Machine Learning in Nigerian Hospitals

TO Atoyebi, RF Olanrewaju, NV Blamah, M Olalere - academia.edu
Malaria disease is the number one cause of death all over the Sub-Sahara world. Data
mining can help extract valuable knowledge from available data in the healthcare sector …

[PDF][PDF] A hybrid model for predicting malaria using data mining techniques

A Aliyu - 2017 - digitallibrary.aun.edu.ng
Data mining is used in extracting rules to predict certain information in many areas of
Information Technology, medical science, biology, education, and human resources. Data …

[引用][C] Reliability of Predictions Using Hybrid Models: The Case of Malaria Incidence Rates in Uganda

P Nabende, FF Bbosa, R Wensonga… - 2020 - Journal of Health Informatics in …