Proposing a machine-learning based method to predict stillbirth before and during delivery and ranking the features: nationwide retrospective cross-sectional study

• 主要な著者: Toktam Khatibi (著者), Elham Hanifi (著者), Mohammad Mehdi Sepehri (著者), Leila Allahqoli (著者)
• フォーマット: 図書
• 出版事項: BMC, 2021-03-01T00:00:00Z.
• 主題: article
• オンライン･アクセス: Connect to this object online.

Abstract Background Stillbirth is defined as fetal loss in pregnancy beyond 28 weeks by WHO. In this study, a machine-learning based method is proposed to predict stillbirth from livebirth and discriminate stillbirth before and during delivery and rank the features. Method A two-step stack ensemble...