Application of machine learning to identify risk factors for Anaemia in pregnancy
| dc.contributor.author | Mukhanya, M. W. | |
| dc.date.accessioned | 2026-04-21T08:38:51Z | |
| dc.date.issued | 2025 | |
| dc.description | Full - text thesis | |
| dc.description.abstract | WHO defines a pregnant woman to be anaemic when the Haemoglobin Concentration value is less than 11g/dl. Reports published by WHO in 2019, 37 % (32 million) of pregnant women globally were Anaemic. These reports also indicate that pregnant women from low and middle-income countries carry the highest burden of prevalence of anaemia. Anaemia negatively affects the mother and both the unborn and born babies. There are research studies that show maternal mortality at delivery, preterm birth, stillbirth, low birth weight, neonatal death, poor development milestones for the babies and postpartum haemorrhage are caused by Anaemia. This research project will utilise data collected from Mariakani and Rabai Hospitals to identify the risk factors of Anaemia and also build a predictive model for early screening of Anaemia. Results from this research could be used to improve the existing maternal health policies and contribute towards attaining sustainable development goals. KEYWORDS: Anaemia, risk factor, Haemoglobin. | |
| dc.identifier.citation | Mukhanya, M. W. (2025). Application of machine learning to identify risk factors for Anaemia in pregnancy [Strathmore University]. https://hdl.handle.net/11071/16412 | |
| dc.identifier.uri | https://hdl.handle.net/11071/16412 | |
| dc.language.iso | en_US | |
| dc.publisher | Strathmore University | |
| dc.title | Application of machine learning to identify risk factors for Anaemia in pregnancy | |
| dc.type | Thesis |
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