Response of the authors to the letter to the editor regarding "Development of a machine learning-based predictive model for long-term adverse outcomes in neonatal bacterial meningitis".
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| Title: | Response of the authors to the letter to the editor regarding "Development of a machine learning-based predictive model for long-term adverse outcomes in neonatal bacterial meningitis". |
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| Authors: | Chen Y; Capital Institute of Pediatrics, Department of Neonatology, Beijing, China; Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China., Wang S; Chinese Academy of Sciences, Institute of Automation, Laboratory of Brain Atlas and Brain-inspired Intelligence, Beijing, China; Chinese Academy of Sciences, Institute of Automation, State Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Beijing, China., Wu J; Capital Medical University, Capital Institute of Pediatrics, Capital Center for Children's Health, Center for Evidence-Based Medicine, Beijing, China., Wang C; Capital Medical University, Capital Institute of Pediatrics, Capital Center for Children's Health, Hemangioma and Interventional Vascular Center, Beijing, China., Li Y; Capital Institute of Pediatrics, Department of Neonatology, Beijing, China., Zou P; Capital Institute of Pediatrics, Department of Neonatology, Beijing, China; Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China., Xiao R; Capital Institute of Pediatrics, Department of Neonatology, Beijing, China; Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China., Zhang N; Seventh Medical Center of PLA General Hospital, Faculty of Pediatrics, Department of Neonatology, Beijing, China., He H; Chinese Academy of Sciences, Institute of Automation, Laboratory of Brain Atlas and Brain-inspired Intelligence, Beijing, China; Chinese Academy of Sciences, Institute of Automation, State Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Beijing, China., Wang Y; Capital Institute of Pediatrics, Department of Neonatology, Beijing, China; Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China. Electronic address: cxswyj@vip.sina.com. |
| Source: | Jornal de pediatria [J Pediatr (Rio J)] 2026 Mar-Apr; Vol. 102 (2), pp. 101525. Date of Electronic Publication: 2026 Mar 16. |
| Publication Type: | Letter |
| Journal Info: | Publisher: Elsevier Editora Ltd Country of Publication: Brazil NLM ID: 2985188R Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1678-4782 (Electronic) Linking ISSN: 00217557 NLM ISO Abbreviation: J Pediatr (Rio J) Subsets: MEDLINE; In Process |
| Database: | MEDLINE Ultimate |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 41771514 AccessLevel: 2 PubType: Editorial & Opinion PubTypeId: editorialOpinion PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Response of the authors to the letter to the editor regarding "Development of a machine learning-based predictive model for long-term adverse outcomes in neonatal bacterial meningitis". – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Chen+Y%22">Chen Y</searchLink>; Capital Institute of Pediatrics, Department of Neonatology, Beijing, China; Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.<br /><searchLink fieldCode="AU" term="%22Wang+S%22">Wang S</searchLink>; Chinese Academy of Sciences, Institute of Automation, Laboratory of Brain Atlas and Brain-inspired Intelligence, Beijing, China; Chinese Academy of Sciences, Institute of Automation, State Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Beijing, China.<br /><searchLink fieldCode="AU" term="%22Wu+J%22">Wu J</searchLink>; Capital Medical University, Capital Institute of Pediatrics, Capital Center for Children's Health, Center for Evidence-Based Medicine, Beijing, China.<br /><searchLink fieldCode="AU" term="%22Wang+C%22">Wang C</searchLink>; Capital Medical University, Capital Institute of Pediatrics, Capital Center for Children's Health, Hemangioma and Interventional Vascular Center, Beijing, China.<br /><searchLink fieldCode="AU" term="%22Li+Y%22">Li Y</searchLink>; Capital Institute of Pediatrics, Department of Neonatology, Beijing, China.<br /><searchLink fieldCode="AU" term="%22Zou+P%22">Zou P</searchLink>; Capital Institute of Pediatrics, Department of Neonatology, Beijing, China; Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.<br /><searchLink fieldCode="AU" term="%22Xiao+R%22">Xiao R</searchLink>; Capital Institute of Pediatrics, Department of Neonatology, Beijing, China; Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.<br /><searchLink fieldCode="AU" term="%22Zhang+N%22">Zhang N</searchLink>; Seventh Medical Center of PLA General Hospital, Faculty of Pediatrics, Department of Neonatology, Beijing, China.<br /><searchLink fieldCode="AU" term="%22He+H%22">He H</searchLink>; Chinese Academy of Sciences, Institute of Automation, Laboratory of Brain Atlas and Brain-inspired Intelligence, Beijing, China; Chinese Academy of Sciences, Institute of Automation, State Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Beijing, China.<br /><searchLink fieldCode="AU" term="%22Wang+Y%22">Wang Y</searchLink>; Capital Institute of Pediatrics, Department of Neonatology, Beijing, China; Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China. Electronic address: cxswyj@vip.sina.com. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%222985188R%22">Jornal de pediatria</searchLink> [J Pediatr (Rio J)] 2026 Mar-Apr; Vol. 102 (2), pp. 101525. <i>Date of Electronic Publication: </i>2026 Mar 16. – Name: TypePub Label: Publication Type Group: TypPub Data: Letter – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Elsevier+Editora+Ltd%22">Elsevier Editora Ltd </searchLink><i>Country of Publication: </i>Brazil <i>NLM ID: </i>2985188R <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1678-4782 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2200217557%22">00217557 </searchLink><i>NLM ISO Abbreviation: </i>J Pediatr (Rio J) <i>Subsets: </i>MEDLINE; In Process |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=41771514 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.jped.2026.101525 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: 101525 Titles: – TitleFull: Response of the authors to the letter to the editor regarding "Development of a machine learning-based predictive model for long-term adverse outcomes in neonatal bacterial meningitis". Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Chen Y – PersonEntity: Name: NameFull: Wang S – PersonEntity: Name: NameFull: Wu J – PersonEntity: Name: NameFull: Wang C – PersonEntity: Name: NameFull: Li Y – PersonEntity: Name: NameFull: Zou P – PersonEntity: Name: NameFull: Xiao R – PersonEntity: Name: NameFull: Zhang N – PersonEntity: Name: NameFull: He H – PersonEntity: Name: NameFull: Wang Y IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: 2026 Mar-Apr Type: published Y: 2026 Identifiers: – Type: issn-electronic Value: 1678-4782 Numbering: – Type: volume Value: 102 – Type: issue Value: 2 Titles: – TitleFull: Jornal de pediatria Type: main |
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