首页|People's Hospital of Guangxi Zhuang Autonomous Region Reports Findings in Machine Learning (An early screening model for preeclampsia: utilizing zero-cost maternal predictors exclusively)
People's Hospital of Guangxi Zhuang Autonomous Region Reports Findings in Machine Learning (An early screening model for preeclampsia: utilizing zero-cost maternal predictors exclusively)
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NETL
NSTL
Springer Nature
New research on Machine Learning is the subject of a report. According to news reporting originating in Nanning, People's Republic of China, by NewsRx journalists, research stated, "To provide a reliable, low-cost screening model for preeclampsia, this study developed an early screening model in a retrospective cohort (25,709 pregnancies) and validated in a validation cohort (1760 pregnancies). A data augmentation method (a-inverse weighted-GMM + RUS) was applied to a retrospective cohort before 10 machine learning models were simultaneously trained on augmented data, and the optimal model was chosen via sensitivity (at a false positive rate of 10%)."
NanningPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesHealth and MedicineMachine LearningObstetricsPreeclampsiaPregnancy ComplicationsWomen's Health
NETL
NSTL
Springer Nature
