Optimizing antimalarial discovery: A robust machine learning framework for chalcone bioactivity prediction using ensemble classifiers and oversampling strategies

The rapid emergence of drug-resistant Plasmodium falciparum necessitates efficient computational tools to prioritize novel antimalarial scaffolds. This study presents a robust machine learning framework for predicting the bioactivity of chalcone derivatives, specifically addressing the challenge of...

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Bibliografske podrobnosti

Principais autores:	Beatrice Nkiruka Iwuala, Mark Madumelu, Abubakar Babando Aliyu, Racheal Gbekele-Oluwa Ayo, Asmau Nasiru Hamza, James Dama Habila
Format:	Artigo
Jezik:	Inglês
Izdano:	Elsevier 2026-06-01
Serija:	Scientific African
Teme:	Machine learning Classification algorithms Molecular fingerprints Antimalarial drug discovery Plasmodium falciparum Ensemble methods
Online dostop:	http://www.sciencedirect.com/science/article/pii/S2468227626002188
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