Enhancing Typhoid Fever Diagnosis Based on Clinical Data Using a Lightweight Machine Learning Metamodel

<b>Background:</b> Typhoid fever remains a significant public health challenge, especially in developing countries where diagnostic resources are limited. Accurate and timely diagnosis is crucial for effective treatment and disease containment. Traditional diagnostic methods, while effective, can be...

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Autores principales:	Fariha Ahmed Nishat, M. F. Mridha, Istiak Mahmud, Meshal Alfarhood, Mejdl Safran, Dunren Che
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	MDPI AG 2025-02-01
Colección:	Diagnostics
Materias:	typhoid fever diagnosis machine learning metamodel clinical data analysis ensemble learning non-invasive diagnostics predictive modeling
Acceso en línea:	https://www.mdpi.com/2075-4418/15/5/562
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