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Development of a machine learning-based predictive model for long-term adverse outcomes in neonatal bacterial meningitis

Crossref DOI link: https://doi.org/10.1016/j.jped.2025.101472

Published Print: 2026-01

Update policy: https://doi.org/10.1016/elsevier_cm_policy

Authors

Chen, Ying https://orcid.org/0009-0008-7088-2527
Wang, Shengpei

Wu, Jing https://orcid.org/0000-0002-5674-3378
Wang, Chi https://orcid.org/0000-0001-7170-568X
Li, Ying https://orcid.org/0009-0006-5197-8721
Zou, Peicen https://orcid.org/0000-0001-7407-3227
Xiao, Ruiqi https://orcid.org/0000-0002-0445-7791
Zhang, Na https://orcid.org/0009-0008-6984-9500
He, Huiguang https://orcid.org/0000-0002-0684-1711
Wang, Yajuan https://orcid.org/0000-0002-8830-7255
Funding

Funding for this research was provided by:

Beijing Municipal Administration of Hospitals (PX2024047)

Beijing Natural Science Foundation (7244289)

Beijing Natural Science Foundation (7232009)

Beijing Municipal Health Commission (-03-02)

National Natural Science Foundation of China (62201569)
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Text and Data Mining valid from 2026-01-01

Version of Record valid from 2025-10-27
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This article is maintained by: Elsevier

Article Title: Development of a machine learning-based predictive model for long-term adverse outcomes in neonatal bacterial meningitis

Journal Title: Jornal de Pediatria

CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.jped.2025.101472

Content Type: article

Copyright: © 2025 The Authors. Published by Elsevier España, S.L.U. on behalf of Sociedade Brasileira de Pediatria.