Artificial Neural Network Model Building in Predicting Maternal Mortality at Chitungwiza Central Hospital, ZimbabweArtificial Neural Network Model Building in Predicting Maternal Mortality at Chitungwiza Central Hospital, Zimbabwe
Year: 2025
Type: article
Abstract: Sustainable Development Goals (SDGs) have identified the reduction of maternal mortality as a key priority at global level. The target is to reduce the global maternal mortality ratio to 70 deaths per 100 000 live births by 2030 and to ensure that no co untry with maternal mortality of more than as twice as the global average (Alemayehu, 2019). Pursuant to this target, every country is required to calculate and achieve its national target by 2030. In 2017, the World Health Organization(WHO) reported that about 810 women died every day due to preventable causes related to pregnancy and childbirth. This number remained consistent throughout the year. Between 2017 and 2 000 the maternal mortality ratio (MMR number of maternal deaths per 100 000 live births) dropped by about 38% worldwide; of which, 94% of all maternal deaths occur in low and lower middle income countries. This provides an insight of variations in maternal mortality exist in high income European countries (Azhar, 2018
DOI: 10.71458/32xz4314
Institutions: Zimbabwe Ezekiel Guti University, Midlands State University
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W4408544669