Quantitative prediction of postpartum hemorrhage in cesarean section on machine learning
Meng Wang,
Gao Yi,
Yunjia Zhang
et al.
Abstract:Background
Cesarean section-induced postpartum hemorrhage (PPH) potentially causes anemia and hypovolemic shock in pregnant women. Hence, it is helpful for obstetricians and anesthesiologists to prepare pre-emptive prevention when predicting PPH occurrence in advance. However, current works on PPH prediction focus on whether PPH occurs rather than assessing PPH amount. To this end, this work studies quantitative PPH prediction with machine learning (ML).
Methods
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