Prediction Models for Intrauterine Growth Restriction Using Artificial Intelligence and Machine Learning: A Systematic Review and Meta-Analysis

Background: IntraUterine Growth Restriction (IUGR) is a global public health concern and has major implications for neonatal health. The early diagnosis of this condition is crucial for obtaining positive outcomes for the newborn. In recent years Artificial intelligence (AI) and machine learning (ML...

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Detalles Bibliográficos
Autores principales: Rescinito, Riccardo, Ratti, Matteo, Payedimarri, Anil Babu, Panella, Massimiliano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Systematic Review
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10252230/
https://www.ncbi.nlm.nih.gov/pubmed/37297757
http://dx.doi.org/10.3390/healthcare11111617

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10252230/
https://www.ncbi.nlm.nih.gov/pubmed/37297757
http://dx.doi.org/10.3390/healthcare11111617

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