Functional gastrointestinal disorders predictors in neonates and toddlers: A machine learning approach to risk assessment

Background: Functional Gastrointestinal Disorders (FGIDs) can pose a great burden on affected children, their families, and the healthcare system. Due to the lack of knowledge about the precise pathophysiology of FGIDs, a proper identification of children at risk to develop FGIDs has never been atte...

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Bibliographic Details
Main Authors:	Flavia Indrio, Elio Masciari, Flavia Marchese, Matteo Rinaldi, Gianfranco Maffei, Ilaria Gangai, Assunta Grillo, Roberta De Benedetto, Enea Vincenzo Napolitano, Isadora Beghetti, Luigi Corvaglia, Antonio Di Mauro, Arianna Aceti
Format:	Article
Language:	English
Published:	Elsevier 2025-01-01
Series:	Heliyon
Subjects:	Functional gastrointestinal disorders Neonatal risk prediction Artificial intelligence
Online Access:	http://www.sciencedirect.com/science/article/pii/S2405844024175470
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Functional gastrointestinal disorders predictors in neonates and toddlers: A machine learning approach to risk assessment

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