A maChine and deep Learning Approach to predict pulmoNary hyperteNsIon in newbornS with congenital diaphragmatic Hernia (CLANNISH): Protocol for a retrospective study

<h4>Introduction</h4> Outcome predictions of patients with congenital diaphragmatic hernia (CDH) still have some limitations in the prenatal estimate of postnatal pulmonary hypertension (PH). We propose applying Machine Learning (ML), and Deep Learning (DL) approaches to fetuses and newb...

Description complète

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Ilaria Amodeo, Giorgio De Nunzio, Genny Raffaeli, Irene Borzani, Alice Griggio, Luana Conte, Francesco Macchini, Valentina Condò, Nicola Persico, Isabella Fabietti, Stefano Ghirardello, Maria Pierro, Benedetta Tafuri, Giuseppe Como, Donato Cascio, Mariarosa Colnaghi, Fabio Mosca, Giacomo Cavallaro
Format:	article
Langue:	EN
Publié:	Public Library of Science (PLoS) 2021
Sujets:	Medicine R Science Q
Accès en ligne:	https://doaj.org/article/6cc919b88fd14fa38fa0a7a614277afb
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Soyez le premier à ajouter un commentaire!

A maChine and deep Learning Approach to predict pulmoNary hyperteNsIon in newbornS with congenital diaphragmatic Hernia (CLANNISH): Protocol for a retrospective study

Documents similaires