Predicting adverse birth outcome among childbearing women in Sub-Saharan Africa: employing innovative machine learning techniques

• Egile Nagusiak: Habtamu Setegn Ngusie (Egilea), Shegaw Anagaw Mengiste (Egilea), Alemu Birara Zemariam (Egilea), Bogale Molla (Egilea), Getanew Aschalew Tesfa (Egilea), Binyam Tariku Seboka (Egilea), Tilahun Dessie Alene (Egilea), Jing Sun (Egilea)
• Formatua: Liburua
• Argitaratua: BMC, 2024-07-01T00:00:00Z.
• Gaiak: article
• Sarrera elektronikoa: Connect to this object online.

Abstract Background Adverse birth outcomes, including preterm birth, low birth weight, and stillbirth, remain a major global health challenge, particularly in developing regions. Understanding the possible risk factors is crucial for designing effective interventions for birth outcomes. Accordingly,...