Combination of XGBoost Analysis and Rule-Based Method for Intrapartum Cardiotocograph Classification

The two major components of a cardiotocograph (CTG) are uterine contraction (UC) and fetal heart rate (FHR) signals. CTG has been widely used to monitor fetal well-being in the past 50 years. The guideline provided by the National Institute of Child Health and Human Development (NICHD) classifies CTG patterns into three categories (I, II, and III) in evaluating the status of a fetus. However, manual interpretation of CTG is time-consuming and is subjected to inter-personal bias. In this study, we combined the rule-based method and eXtreme Gradient Boosting (XGBoost) analysis in classifying CTG patterns. Because of the persistent controversies about the Category II of NICHD, XGBoost analysis was used to classify it into IIa and IIb. A total of 68 pregnant women were enrolled in this study. Three categories (I, II, and III) were consistent in both manual interpretation by clinicians and our algorithm across all categories, and the average Kappa was about 0.72. The probability of fetal distress (FD) was 28.8% and 71.2% in the categories IIa and IIb, respectively. These findings show the proposed method has the potential to provide a clinical assistant tool to monitor fetal well-being and has high potential to be an assistive and warning system to reduce the burden of medical staff.