AIMC Topic: Ghana

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Soil geochemistry and contamination zoning in Northeastern Ghana: insights from the Bongo and Talensi districts.

Environmental geochemistry and health
Reliable geochemical baselines are largely absent for northern Ghana, limiting efforts to distinguish natural element variability from human-induced contamination. This study addresses that gap by evaluating soil geochemical compositions in the Bongo...

Equitable AI: Exploring the role of gender in poverty estimation models using geospatial data.

PloS one
Household surveys have been the foundation for poverty measurement in developing countries for the past half-century, but the spatial and temporal gaps in these survey data often limit how well anti-poverty programs can be targeted, monitored, or eva...

BamClassifier: a machine learning method for assessing iron deficiency.

Scientific reports
Iron deficiency (ID) is a well-known cause of anaemia and could lead to adverse clinical and functional impairments. However, ID is under-diagnosed due to non-specific symptoms, difficulties in interpreting ambiguous assessment outcomes and suboptima...

Prediction of caesarean section birth using machine learning algorithms among pregnant women in a district hospital in Ghana.

BMC pregnancy and childbirth
BACKGROUND: Machine learning algorithms may contribute to improving maternal and child health, including determining the suitability of caesarean section (CS) births in low-resource countries. Despite machine learning algorithms offering a more robus...

Moving beyond the noise: geospatial modelling of urban sound environments in a sub-Saharan African city.

Scientific reports
Cities encompass a mixture of artificial, human, animal, and nature-based sounds, which through long and short-term exposures, can impact on physical and mental health. Yet, most epidemiological research has focused on only transportation noise, leav...

Principles for enhancing trust in artificial intelligence systems among medical imaging professionals in Ghana: A nationwide cross-sectional study.

Radiography (London, England : 1995)
INTRODUCTION: To realise the full potential of artificial intelligence (AI) systems in medical imaging, it is crucial to address challenges, such as cyberterrorism to foster trust and acceptance. This study aimed to determine the principles that enha...

Gut microbiota shift in Ghanaian individuals along the migration axis: the RODAM-Pros cohort.

Gut microbes
Migration is associated with a substantial change in environmental exposures and health outcomes. We aimed to investigate the shift in gut microbiota composition and the associations with cardiometabolic outcomes in the RODAM-Pros cohort spanning mul...

Nutritional predictors of lymphatic filariasis progression: Insights from a machine learning approach.

PloS one
Lymphatic filariasis (LF) is a mosquito-borne neglected tropical disease that causes disfiguring of the affected extremities, often leading to permanent disability and stigma. Described as a disease of poverty, the impact of socioeconomic indicators ...

Predictive models and determinants of mortality among T2DM patients in a tertiary hospital in Ghana, how do machine learning techniques perform?

BMC endocrine disorders
BACKGROUND: The increasing prevalence of type 2 diabetes mellitus (T2DM) in lower and middle - income countries call for preventive public health interventions. Studies from Africa including those from Ghana, consistently reveal high T2DM-related mor...

A supervised machine learning statistical design of experiment approach to modeling the barriers to effective snakebite treatment in Ghana.

PLoS neglected tropical diseases
BACKGROUND: Snakebite envenoming is a serious condition that affects 2.5 million people and causes 81,000-138,000 deaths every year, particularly in tropical and subtropical regions. The World Health Organization has set a goal to halve the deaths an...