Machine Learning Prediction Models for Neurodevelopmental Outcome After Preterm Birth:A Scoping Review and New Machine Learning Evaluation Framework

Autor: Menne R, van Boven, Celina E, Henke, Aleid G, Leemhuis, Mark, Hoogendoorn, Anton H, van Kaam, Marsh, Königs, Jaap, Oosterlaan

Publikováno v: van Boven, M R, Henke, C E, Leemhuis, A G, Hoogendoorn, M, van Kaam, A H, Königs, M & Oosterlaan, J 2022, ' Machine Learning Prediction Models for Neurodevelopmental Outcome After Preterm Birth : A Scoping Review and New Machine Learning Evaluation Framework ', Pediatrics, vol. 150, no. 1, pp. 1-15 . https://doi.org/10.1542/peds.2021-056052
van Boven, M R, Henke, C E, Leemhuis, A G, Hoogendoorn, M, van Kaam, A H, Königs, M & Oosterlaan, J 2022, ' Machine Learning Prediction Models for Neurodevelopmental Outcome After Preterm Birth : A Scoping Review and New Machine Learning Evaluation Framework ', Pediatrics, vol. 150, no. 1 . https://doi.org/10.1542/peds.2021-056052

BACKGROUND AND OBJECTIVES Outcome prediction of preterm birth is important for neonatal care, yet prediction performance using conventional statistical models remains insufficient. Machine learning has a high potential for complex outcome prediction.

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https://research.vu.nl/ws/files/215464497/Machine_Learning_Prediction_Models_for_Neurodevelopmental_Outcome_After_Preterm_Birth.pdf