A5060444121- Child Nutrition and Water Access
- Global Maternal and Child Health
- Healthcare Systems and Reforms
- Public Health and Nutrition
- HIV, Drug Use, Sexual Risk
- Global Health Care Issues
- HIV/AIDS Research and Interventions
- Statistical Methods and Bayesian Inference
- COVID-19 epidemiological studies
- Sex work and related issues
- Poverty, Education, and Child Welfare
- Pregnancy and preeclampsia studies
- Financial Distress and Bankruptcy Prediction
- COVID-19 diagnosis using AI
- Demographic Trends and Gender Preferences
- Statistical Methods and Inference
- COVID-19 Pandemic Impacts
- Food Security and Health in Diverse Populations
- Statistical Methods in Epidemiology
- Advanced Statistical Modeling Techniques
- HIV/AIDS Impact and Responses
- Nursing Diagnosis and Documentation
- Efficiency Analysis Using DEA
- Imbalanced Data Classification Techniques
- Maternal and Perinatal Health Interventions
University of Rwanda
2013-2025
University of Kigali
2023-2025
Rwanda Agriculture Board
2024
Makerere University
2023
Utrecht University
2013
Rwanda reported a stunting rate of 33% in 2020, decreasing from 38% 2015; however, remains an issue. Globally, child deaths malnutrition stand at 45%. The best options for the early detection and treatment should be made community policy priority, health services remain Hence, this research aimed to develop model predicting Rwandan children.The Demographic Health Survey 2019-2020 was used as secondary data. Stratified 10-fold cross-validation used, different machine learning classifiers were...
Missing data is commonplace in clinical databases, which are being increasingly used for research. Without giving any regard to missing data, results from analysis may become biased and unrepresentative. Clinical databases contain mainly categorical variables. This study aims assess the methods imputation We utilized extracted paper-based maternal health records Kawempe National Referral Hospital, Uganda. compared following an empirical analysis: Mode, K-Nearest Neighbors (KNN), Random...
Stunting is a serious public health concern in Rwanda, affecting around 33.3% of children under five 2020. The researchers have employed machine learning algorithms to predict stunting Rwanda; however, few studies used ANNs, despite their strong capacity stunting. purpose this study was Rwanda using ANNs and the most recent DHS data from 2020 dataset train test an ANN model for predicting children. dataset, which included various child, parental, socio-demographic characteristics, split into...
With the advancement in technology, tax base Rwanda has become broader, and as a result, fraud is growing. Depending on dataset used, detection experts researchers have used different methods to identify questionable cases. This paper aims predict features of using most robust supervised machine-learning model. research provides context where expert can use model, an implemented model offers instant feedback expert. We evaluate machine learning models such Artificial Neural Network, Logistic...
Abstract Background Since the outbreak of COVID-19 pandemic in Rwanda, a vast amount SARS-COV-2/COVID-19-related data have been collected including testing and hospital routine care data. Unfortunately, those are fragmented silos with different structures or formats cannot be used to improve understanding disease, monitor its progress, generate evidence guide prevention measures. The objective this project is leverage artificial intelligence (AI) science techniques harmonizing datasets...
Background Globally, men who have sex with (MSM) continue to bear a disproportionately high burden of HIV infection. Rwanda experiences mixed epidemic, which is generalized in the adult population, aspects concentrated epidemic among certain key populations at higher risk infection, including MSM. Limited data exist estimate population size MSM national scale; hence, an important piece missing determining denominators use estimates for policy makers, program managers, and planners...
in Rwanda, the estimated out-of-pocket health expenditure has been increased from 24.46% 2000 to 26% 2015. Despite existence of guideline estimation expenditures provided by WHO (2018), still have difficulties many countries including Rwanda.the purpose this paper was figure out best model which predicts Rwanda during process considering various techniques machine learning using Integrated Living Conditions Surveys (EICV5) 14580 households (2018).our findings presented predict with higher...
Although the policy in Rwanda aims at ensuring quality healthcare, a portion of Rwandan population still does not have access to it due lack health insurance. This study investigates impact insurance on healthcare utilization all 30 administrative districts Rwanda, using secondary data from 5th Integrated Household Living Conditions Survey (EICV 5) with total 14,580 households. A logistic regression model was used evaluate effects utilization, and decision tree adopted categorize based use...
Abstract Background Stunting among children under 5 years of age remains a worldwide concern, with 148.1 million (22.3%) stunted in 2022. The recent 2019/2020 Rwanda Demographic Health Survey (RDHS) revealed that the prevalence stunting five was 33.5%. In Rwanda, there is no sufficient evidence on status to guide prioritized interventions at sector level, lowest administrative unit for implementing development initiatives. This study aimed provide reliable estimates level. Methods this...
Background Adverse pregnancy outcomes pose significant risk to maternal and neonatal health, contributing morbidity, mortality, long-term developmental challenges. This study aimed predict these in Rwanda using supervised machine learning algorithms. Methods cross-sectional utilized data from the Demographic Health Survey (RDHS, 2019–2020) involving 14,634 women. K-fold cross-validation (k = 10) synthetic minority oversampling technique (SMOTE) were used manage dataset partitioning class...
In East Africa, 39% of all children were stunted in 2016. Rwanda reported the second highest rate at 37.7%. Globally, deaths from malnutrition stand 45% child deaths, creating an economic handicap for countries. According to World Health Organization's (WHO) goal reduce by 3.9% per year, countries must define appropriate strategies. Although related research has been conducted Rwanda, issue prevails. This study assesses stunting with multiple factors, aim revealing system-wide impact food...
In 2007 Rwanda launched a campaign to promote 3 children families and program of community based health services improve reproductive health. This paper argues that mixed gender offspring is still an important insurance for old age in arrive at the desired composition women might have progress beyond parity 3. The analyses are twofold. first progression desire given living children. second specific replacement intention following loss last or only son daughter. Using Demographic Health...
<ns3:p>Background Stunting is a serious public health concern in Rwanda, affecting around 33.3% of children under the age five 2020. Several examples research have employed machine learning algorithms to predict stunting Rwanda; however, no study used artificial neural networks (ANNs), despite their strong capacity stunting. The purpose this was Rwanda using ANNs and most recent Demographic Health Survey (DHS) data from Methods We multilayer perceptron (MLP) architecture train test ANN model...
Background HIV surveillance among key populations is a priority in all epidemic settings. Female sex workers (FSWs) globally as well Rwanda are disproportionately affected by the epidemic; hence, and AIDS National Strategic Plan (2018-2024) has adopted regular of population size estimation (PSE) FSWs every 2-3 years. Objective We aimed at estimating, for fourth time, street- venue-based sexually exploited minors aged ≥15 years Rwanda. Methods In August 2022, 3-source capture-recapture method...
<title>Abstract</title> Background In Rwanda, the prevalence of childhood stunting has slightly decreased over past five years, from 38% to about 33% today. It is evident whether Rwanda's multi-sectorial approach reducing child consistent with available scientific knowledge. The study was examine benefits national nutrition programs on reduction under two years in Rwanda using ML classifiers. Methods Data DHS 2015–2020, MEIS and LODA household survey were used. model constructed algorithms:...
The COVID-19 pandemic along with its devastating impact on human lives has disrupted the socioeconomic situation worldwide. Rwanda adopted lockdowns and other measures to prevent spread of pandemic. Recent studies documented macro-level socio-economic but a household's daily life been scarcely especially in low-and-middle-income countries. This work describes interplay between multiple factors assess Rwandan population at micro-level (household). Data from country-wide community survey...
Abstract Background In Rwanda, the prevalence of childhood stunting has slightly decreased over past five years, from 38% in 2015 to about 33% 2020. It is evident whether Rwanda's multi-sectorial approach reducing child consistent with available scientific knowledge. The study was examine benefits national nutrition programs on reduction under two years Rwanda using machine learning classifiers. Methods Data DHS 2015–2020, MEIS and LODA household survey were used. By evaluating best method...
Abstract Purpose: In Rwanda, childhood stunting is a major public health problem. Earlier studies employed traditional statistical approaches to identify causal factors stunting, and little known about the uses effectiveness of machine learning (ML) algorithms that may risk for variety conditions based on complex data. Methods: This study examines usefulness in predicting children under age five using data from 2020 Rwanda Demographic Health Survey. Random Forest was utilized feature...
Objectives: Missing data is commonplace in clinical databases, which are being increasingly used for research. These databases contain mainly categorical variables. The questionable aspect the best imputation method data.Materials and methods: We utilized extracted from paper-based maternal health records Kawempe National Referral Hospital, Uganda. compared following methods an empirical analysis: Mode, K-Nearest Neighbors (KNN), Random Forest (RF), Sequential Hot-Deck (SHD), Multiple...
In Rwanda, more than 90% of the population is insured for health care. Despite comprehensiveness insurance coverage in some services at partner institutions are not available, causing patients to pay unintended cost. We aimed analyze effect on care utilization and factors associated with use Rwanda. This an analysis secondary data from Rwanda integrated living condition survey 2016-2017. The gathered 14580 households, decision tree multilevel logistic regression models were applied. Among...
Abstract Background: In 2008, Rwanda decided to enhance its community health program in order further scale up the system effectiveness. One of components is community-based family planning. Between 2010 and 2015, proportion women using contraception from workers (CHWs) increased threefold. This study aims at identify socio-economic factors associated with choice CHWs as contraceptive providers period 2010-2015. Methods: The uses a pooled dataset 2015 Demographic Health Surveys. It...
Abstract Purpose: Preterm Birth (PTB) is one of the leading causes neonatal mortality in Uganda. Machine Learning (ML) can be used to identify women at risk PTB time for medical intervention and adequate preparation by mothers. Methods: We utilized data from paper-based maternal health records Kawempe National Referral Hospital, A case-control method was employed, where every woman who experienced a PTB, without delivered same day selected as control. Treatment missing done using Random...