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Development and validation of an interpretable machine learning model for early hospital-based differentiation of chikungunya and dengue fever using routine clinical data

Crossref DOI link: https://doi.org/10.1186/s12879-026-13778-6

Published Online: 2026-06-23

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Zhang, Lin

Liu, Jing

Mai, Jia-Liang

Yang, Quan

Zhao, Jia-Yi

Hong, Meng-Hui
License Information

Text and Data Mining valid from 2026-06-23

Version of Record valid from 2026-09-07
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Article History

Received: 21 March 2026

Accepted: 4 June 2026

First Online: 23 June 2026

Declarations

Ethical approval: This study was approved by the Ethics Committee of The Affiliated Foshan Women and Children Hospital, Guangdong Medical University (approval number: FSFY-MEC-2026-062). The study was conducted in accordance with the ethical principles of the Declaration of Helsinki. The requirement for informed consent was waived by the Ethics Committee because this was a retrospective study using anonymized clinical data.

Consent for publication: Not applicable.

Competing interests: The authors declare no competing interests.

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