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

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 effec...

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Bibliographic Details
Main Authors: Fariha Ahmed Nishat, M. F. Mridha, Istiak Mahmud, Meshal Alfarhood, Mejdl Safran, Dunren Che
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Diagnostics
Subjects:
typhoid fever diagnosis
machine learning metamodel
clinical data analysis
ensemble learning
non-invasive diagnostics
predictive modeling
Online Access:https://www.mdpi.com/2075-4418/15/5/562
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