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Using Vital Signs for the Early Prediction of Necrotizing Enterocolitis in Preterm Neonates with Machine Learning.

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Title: Using Vital Signs for the Early Prediction of Necrotizing Enterocolitis in Preterm Neonates with Machine Learning.
Authors: Verhoeven R; Department of Surgery, Division of Pediatric Surgery, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001, 9700 RB Groningen, The Netherlands.; Department of Neonatology, Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001, 9700 RB Groningen, The Netherlands., Kupers T; Department of Neonatology, Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001, 9700 RB Groningen, The Netherlands.; Researchable, Zernikepad 12, 9747 AN Groningen, The Netherlands., Brunsch CL; Department of Neonatology, Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001, 9700 RB Groningen, The Netherlands., Hulscher JBF; Department of Surgery, Division of Pediatric Surgery, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001, 9700 RB Groningen, The Netherlands., Kooi EMW; Department of Neonatology, Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001, 9700 RB Groningen, The Netherlands.
Source: Children (Basel, Switzerland) [Children (Basel)] 2024 Nov 28; Vol. 11 (12). Date of Electronic Publication: 2024 Nov 28.
Publication Type: Journal Article
Journal Info: Publisher: MDPI AG Country of Publication: Switzerland NLM ID: 101648936 Publication Model: Electronic Cited Medium: Print ISSN: 2227-9067 (Print) Linking ISSN: 22279067 NLM ISO Abbreviation: Children (Basel) Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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  Data: Using Vital Signs for the Early Prediction of Necrotizing Enterocolitis in Preterm Neonates with Machine Learning.
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  Data: <searchLink fieldCode="AU" term="%22Verhoeven+R%22">Verhoeven R</searchLink>; Department of Surgery, Division of Pediatric Surgery, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001, 9700 RB Groningen, The Netherlands.; Department of Neonatology, Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001, 9700 RB Groningen, The Netherlands.<br /><searchLink fieldCode="AU" term="%22Kupers+T%22">Kupers T</searchLink>; Department of Neonatology, Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001, 9700 RB Groningen, The Netherlands.; Researchable, Zernikepad 12, 9747 AN Groningen, The Netherlands.<br /><searchLink fieldCode="AU" term="%22Brunsch+CL%22">Brunsch CL</searchLink>; Department of Neonatology, Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001, 9700 RB Groningen, The Netherlands.<br /><searchLink fieldCode="AU" term="%22Hulscher+JBF%22">Hulscher JBF</searchLink>; Department of Surgery, Division of Pediatric Surgery, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001, 9700 RB Groningen, The Netherlands.<br /><searchLink fieldCode="AU" term="%22Kooi+EMW%22">Kooi EMW</searchLink>; Department of Neonatology, Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001, 9700 RB Groningen, The Netherlands.
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  Data: <searchLink fieldCode="JN" term="%22101648936%22">Children (Basel, Switzerland)</searchLink> [Children (Basel)] 2024 Nov 28; Vol. 11 (12). <i>Date of Electronic Publication: </i>2024 Nov 28.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22MDPI+AG%22">MDPI AG </searchLink><i>Country of Publication: </i>Switzerland <i>NLM ID: </i>101648936 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Print <i>ISSN: </i>2227-9067 (Print) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2222279067%22">22279067 </searchLink><i>NLM ISO Abbreviation: </i>Children (Basel) <i>Subsets: </i>PubMed not MEDLINE
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        Value: 10.3390/children11121452
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        Text: English
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      – TitleFull: Using Vital Signs for the Early Prediction of Necrotizing Enterocolitis in Preterm Neonates with Machine Learning.
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              Text: 2024 Nov 28
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