Machine learning and meningitis prediction in pediatric invasive pneumococcal disease: a retrospective single-center study

Abstract Objective To analyze the clinical characteristics of children with invasive pneumococcal disease (IPD) admitted to Kunming Children’s Hospital from 2020 to 2024, and to develop a risk stratification model for pneumococcal meningitis among children with confirmed or highly suspected IPD usin...

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Autori principali:	Yonghan Luo, Mingbiao Ma, Mengyue Tong, Xin Ma, Deyuan Jiang, Hao Wu, Lijiao Yuan, Yan Guo, Ying Zhu, Haifeng Jin, Penghao Cui, Ruonan Li, Qingping Tang, Yanchun Wang
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	BMC 2026-04-01
Serie:	BMC Infectious Diseases
Soggetti:	Invasive pneumococcal disease Meningitis Pediatrics Machine learning Nomogram
Accesso online:	https://doi.org/10.1186/s12879-026-13345-z
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