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Ghana

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Modeling vehicle ownership with machine learning techniques in the Greater Tamale Area, Ghana.

PloS one
Vehicle ownership modeling and prediction is a crucial task in the transportation planning processes which, traditionally, uses statistical models in the modeling process. However, with the advancement in computing power of computers and Artificial I...

Radiographers' perspectives on the emerging integration of artificial intelligence into diagnostic imaging: The Ghana study.

Journal of medical radiation sciences
INTRODUCTION: The integration of artificial intelligence (AI) systems into medical imaging is advancing the practice and patient care. It is thought to further revolutionise the entire field in the near future. This study explored Ghanaian radiograph...

Use of a deep learning and random forest approach to track changes in the predictive nature of socioeconomic drivers of under-5 mortality rates in sub-Saharan Africa.

BMJ open
OBJECTIVES: We used machine learning algorithms to track how the ranks of importance and the survival outcome of four socioeconomic determinants (place of residence, mother's level of education, wealth index and sex of the child) of under-5 mortality...

Characterisation of urban environment and activity across space and time using street images and deep learning in Accra.

Scientific reports
The urban environment influences human health, safety and wellbeing. Cities in Africa are growing faster than other regions but have limited data to guide urban planning and policies. Our aim was to use smart sensing and analytics to characterise the...

Phenotyping urban built and natural environments with high-resolution satellite images and unsupervised deep learning.

The Science of the total environment
Cities in the developing world are expanding rapidly, and undergoing changes to their roads, buildings, vegetation, and other land use characteristics. Timely data are needed to ensure that urban change enhances health, wellbeing and sustainability. ...

Assessing the impact of climate variability on maize yields in the different regions of Ghana-A machine learning perspective.

PloS one
Climate variability has become one of the most pressing issues of our time, affecting various aspects of the environment, including the agriculture sector. This study examines the impact of climate variability on Ghana's maize yield for all agro-ecol...

Predictive analysis on the factors associated with birth Outcomes: A machine learning perspective.

International journal of medical informatics
BACKGROUND: Recent studies reveal that around 1.9 million stillbirths occur annually worldwide, with Sub-Saharan Africa having among the highest cases. Some Sub-Saharan African countries, including Ghana, failed to meet Millennium Development Goal 5 ...

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...

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...