A machine learning approach to predict mortality and neonatal persistent pulmonary hypertension in newborns with congenital diaphragmatic hernia. A retrospective observational cohort study.
| Publicado en: | European Journal of Pediatrics Vol. 184; no. 4; pp. 1 - 13 |
|---|---|
| Autores principales: | , , , , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Apr2025
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=183595655&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 183595655 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 03406199 CR1 jtl: European Journal of Pediatrics issn: 03406199 maglogo: N pubinfo: dt: Apr2025 vid: 184 iid: 4 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 183595655 10.1007/s00431-025-06073-0 183595655 ppf: 1 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: A machine learning approach to predict mortality and neonatal persistent pulmonary hypertension in newborns with congenital diaphragmatic hernia. A retrospective observational cohort study. aug: au: Conte, Luana Amodeo, Ilaria De Nunzio, Giorgio Raffaeli, Genny Borzani, Irene Persico, Nicola Griggio, Alice Como, Giuseppe Colnaghi, Mariarosa Fumagalli, Monica Cascio, Donato Cavallaro, Giacomo affil: https://ror.org/044k9ta02 Department of Physics and Chemistry, Università Degli Studi Di Palermo, Palermo, Italy sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
|---|