Publisher
Springer Nature Singapore
Reference16 articles.
1. Alam SMB, Patwary MJA, Hassan M (2021) Birth mode prediction using bagging ensemble classifier: a case study of Bangladesh. In: 2021 International conference on information and communication technology for sustainable development (ICICT4SD)
2. Harrison MS, Garces AL, Goudar SS et al (2020) Cesarean birth in the global network for women’s and children’s health research: trends in utilization, risk factors, and subgroups with high cesarean birth rates. Reprod Health 17(Suppl 3):165
3. Rahman S et al (2021) Risk prediction with machine learning in cesarean section: optimizing healthcare operational decisions. Sig Process Tech Comput Health Inf 293–314
4. Islam MN, Mahmud T, Khan NI, Mustafina SN, Islam AKMN (2016) Exploring machine learning algorithms to find the best features for predicting modes of Childbirth. In: 2016 International conference on computing communication control and automation (ICCUBEA)
5. Abbas S, Riaz R, Kazmi S, Rizvi S, Kwon S (2018) cause analysis of cesarean sections and application of machine learning methods for classification of birth data, pp 1–1. IEEE Access. https://doi.org/10.1109/ACCESS.2018.2879115