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dc.contributor.authorWamala, Edgar Watson
dc.contributor.authorKyanzi, Hassan Musisi
dc.contributor.authorAsiimwe, Brenda Angel
dc.contributor.authorTindyebwa, Fortunate Allan
dc.date.accessioned2022-05-05T08:37:51Z
dc.date.available2022-05-05T08:37:51Z
dc.date.issued2022-02-09
dc.identifier.citationWamala, E. W., Kyanzi, H. M., Asiimwe, B. A., & Tindyebwa, F. A. (2022). Maternal mortality rate prediction and advisory system. (Unpublished Undergraduate Dissertation). Makerere University, Kampala, Uganda.en_US
dc.identifier.urihttp://hdl.handle.net/20.500.12281/12145
dc.descriptionA project report submitted to the School of Computing and Informatics Technology in partial fulfillment of the requirements for the award of the degree of Bachelor of Science in Software Engineering of Makerere University.en_US
dc.description.abstractW.H.O defines Maternal mortality as the annual number of female deaths from any cause related to or aggravated by pregnancy or its management (excluding accidental or incidental causes) during pregnancy and childbirth or within 42 days of termination of pregnancy, irrespective of the duration and site of the pregnancy.[1]. The maternal mortality ratio is the yearly number of maternal deaths from any cause related to or aggravated by pregnancy or its management (excluding accidental or incidental causes) during pregnancy, childbirth, or within 42 days of termination of pregnancy, per 100,000 live births per year. The maternal mortality rate is the number of maternal deaths in a population divided by the number of women of reproductive age. It captures the likelihood of both becoming pregnant and dying during pregnancy (including deaths up to six weeks after delivery).[2] The Maternal Mortality Rate Prediction and Advisory system tackles this maternal mortality problem by combining expertise in maternal health care, data analytics, modeling and simulation. Most maternal health professionals agree that maternal mortality can be controlled by timely and proper interventions. We started by identifying the reasons behind big numbers in impoverished regions of Uganda. We started with regions with biggest numbers of maternal mortality rates in previous years and then look at those regions with least numbers and may be the factors attributing to the small numbers and may be advise other regions to emulate them. This Maternal Mortality Prediction and Advisory System comprises three parts: prediction module, a web portal, and an SMS messaging system. The Prediction module will be used to make forecasts of maternal mortality rates of different regions. This will enable concerned authorities to facilitate prioritization of resource allocation to different regions of Uganda and optimize the impact of scarce resources in various areas with high maternal deaths. The prediction module applies data analytics to provide projections of maternal mortality impact and scalability of evidence based interventions on maternal mortality .[3]. This book has four documents a software design document, a software requirements specification, an implementation report and a manual for the Maternal Mortality Rate Prediction and Advisory System.en_US
dc.language.isoenen_US
dc.publisherMakerere Universityen_US
dc.subjectmaternal mortalityen_US
dc.subjectpredictionen_US
dc.subjectadvisory systemen_US
dc.subjectsoftware applicationen_US
dc.subjectsoftware designen_US
dc.titleMaternal mortality rate prediction and advisory systemen_US
dc.typeThesisen_US


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