Prediction of measles patients using machine learning classifiers: a comparative study

Prediction of measles patients using machine learning classifiers: a comparative study

Abstract Background Measles has high primary reproductive number, extremely infectious and ranked second to malaria in terms of disease burden in Ghana. Owing to the disease’s high infectious rate, making early diagnosis based on an accurate system can help limit the spread of the disease. Studies h...

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Bibliographic Details
Main Authors: Robert Gyebi, Gabriel Asare Okyere, Emmanuel Kwaku Nakua, Franklin Aseidu-Bekoe, Jane Serwaa Akoto Nti, Emmanuel Owusu Ansah, Felix Agyemang Opoku
Format: Article
Language:English
Published: SpringerOpen 2023-07-01
Series:Bulletin of the National Research Centre
Subjects:
Measles
Prediction
Machine learning
Classification techniques
Prediction accuracy
Online Access:https://doi.org/10.1186/s42269-023-01079-w

Internet

https://doi.org/10.1186/s42269-023-01079-w

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