APA (7th ed.) Citation

M, Y., D, L., Y, L., X, L., Z, B., & Z, L. (2025). An explainable machine learning model in predicting vaginal birth after cesarean section. The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians, 38(1), 2546544. https://doi.org/10.1080/14767058.2025.2546544

Chicago Style (17th ed.) Citation

M, Yang, Long D, Li Y, Liu X, Bai Z, and Li Z. "An Explainable Machine Learning Model in Predicting Vaginal Birth After Cesarean Section." The Journal of Maternal-fetal & Neonatal Medicine : The Official Journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians 38, no. 1 (2025): 2546544. https://doi.org/10.1080/14767058.2025.2546544.

MLA (9th ed.) Citation

M, Yang, et al. "An Explainable Machine Learning Model in Predicting Vaginal Birth After Cesarean Section." The Journal of Maternal-fetal & Neonatal Medicine : The Official Journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians, vol. 38, no. 1, 2025, p. 2546544, https://doi.org/10.1080/14767058.2025.2546544.