Ultrasound-based machine learning models for assisting the prediction of neonatal size and mode of delivery.
Background: Elective Cesarean surgeries (CSs) rates continue to rise worldwide, prompting renewed interest in predictors of prenatal biometrics, which have a central role in recommendations for elective CS. Objective: To develop machine learning (ML) models for predicting neonatal anthropometric mea...
| Publicado en: | Therapeutic Advances in Reproductive Health Vol. 20; pp. 1 - 13 |
|---|---|
| Autores principales: | , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
7/29/2026
|
| Acceso en línea: | Ver este registro en EBSCOhost |