[HTML][HTML] 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 …

Classification of Malaria Complication Using CART (Classification and Regression Tree) and Naïve Bayes

R Irmanita, SS Prasetiyowati, Y Sibaroni - Jurnal RESTI (Rekayasa …, 2021 - jurnal.iaii.or.id
Malaria is a disease caused by the Plasmodium parasite that transmitted by female
Anopheles mosquitoes. Malaria can become a dangerous disease if late have the medical …

[HTML][HTML] Risk assessment of imported malaria in China: a machine learning perspective

S Yang, R Li, S Yan, H Yang, Z Cao, L Zhang, J Xue… - BMC Public Health, 2024 - Springer
Abstract Background Following China's official designation as malaria-free country by WHO,
the imported malaria has emerged as a significant determinant impacting the malaria …

[PDF][PDF] Machine learning for artemisinin resistance in malaria treatment across in vivo-in vitro platforms

H Zhang, J Guo, H Li, Y Guan - Iscience, 2022 - cell.com
Drug resistance has been rapidly evolving with regard to the first-line malaria treatment,
artemisinin-based combination therapies. It has been an open question whether predictive …

[HTML][HTML] Modeling plasmodium falciparum diagnostic test sensitivity using machine learning with histidine-rich Protein 2 variants

CT Ford, GS Alemayehu, K Blackburn… - Frontiers in Tropical …, 2021 - frontiersin.org
Malaria, predominantly caused by Plasmodium falciparum, poses one of largest and most
durable health threats in the world. Previously, simplistic regression-based models have …

Application of Machine Learning for Detection and Prediction of Malaria: A Review

M Apetorgbor, V Wankhede, K Dakhare… - … for Innovation in …, 2024 - ieeexplore.ieee.org
Mosquitoes carries a parasitic infection that affects millions of peoples globally. The initial
and meticulous prediction of outbursts, patient verdict, and treatment enhancement can all …

Extreme phenotype sampling improves lasso and random forest marker selection for complex traits

C John, W Muchero, S Emrich - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
Most attempts to fit a supervised machine learning (ML) model in bioinformatics try to predict
the full range of trait or response values. While such prediction tasks effectively capture the …

Machine learning applied to prediction, control and planning from dynamic epidemiological models

O Bent - 2020 - ora.ox.ac.uk
We are ever aware of the global impact of infectious disease transmission in shaping the
reality of the world around us. For much of human existence transmitted infections have …

Predicting Dihydroartemisinin Resistance in Plasmodium falciparum using Pathway Activity Inference

N Lawford, JH Chan - CSBio'20: Proceedings of the Eleventh …, 2020 - dl.acm.org
Drug resistance threatens the effectiveness of treatments of infectious diseases, particularly
on the global scale where mutation is rapid, mechanisms of resistance are developing or …