Prediction of Neurodevelopmental Outcomes in Very Preterm Infants: Comparing Machine Learning Methods to Logistic Regression
In this population-based cohort of very preterm infants, RF was superior to conventional LR in prediction of NDI at 3 years corrected age. Accurate prediction of preterm infants at risk of NDI enables early referrals for intervention programs and resources allocation toward those who are most likely to benefit.
Authors
- Alessandro Guida (ORCID: https://orcid.org/0000-0002-7160-750X)
- Jehier K. Afifi (ORCID: https://orcid.org/0000-0001-7651-3054)
- Tahani Ahmad (ORCID: https://orcid.org/0000-0001-9885-6090)
- Samuel A. Stewart (ORCID: https://orcid.org/0000-0001-6299-7967)
- Michael John Vincer (ORCID: https://orcid.org/0000-0001-8119-3286)
Institutions
- Dalhousie University (CA)
Publication Details
- Journal
- Children
- Published
- 2024-12-12
- DOI
- https://doi.org/10.3390/children11121512
- Citations
- 3
- Primary Topic
- Neonatal Respiratory Health Research
- Type
- article
- Field-Weighted Citation Impact
- 1.26