A Machine Learning Approach to Predict MRI Brain Abnormalities in Preterm Infants Using Clinical Data
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-34953-9_33
Reference40 articles.
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3. Johnson, S., et al.: Neurodevelopmental outcomes following late and moderate prematurity: a population-based cohort study. Arch. Dis. Child. Fetal Neonatal Ed. 100, F301–F308 (2015). https://doi.org/10.1136/archdischild-2014-307684
4. Rogers, E.E., Hintz, S.R.: Early neurodevelopmental outcomes of extremely preterm infants. Semin. Perinatol. 40, 497–509 (2016). https://doi.org/10.1053/j.semperi.2016.09.002
5. Bowe, A.K., Lightbody, G., Staines, A., Murray, D.M.: Big data, machine learning, and population health: predicting cognitive outcomes in childhood. Pediatr. Res. 93, 300–307 (2023). https://doi.org/10.1038/s41390-022-02137-1
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