Data Science Africa (DSA)  has awarded us a research grant, through their “Africa Artificial Intelligence (AI) Research Award 2022 Innovation Funding for Early Career Researchers” . This award is meant to enable us to execute a project titled “Enterprise Medical Imaging: Automatic Classification of Radiological Medical Images for Efficient and Effective Radiological Workflows in Public Health Facilities”. The scope of work associated with this grant is linked to our broader Enterprise Medical Imaging in Zambia project. In essence, the research grant will complement the Google Research-funded project titled “Exploring the Use of Enterprise Medical Imaging and Artificial Intelligence for Efficient and Effective Radiological Workflows in Public Health Facilities in Zambia” .
About the DSA AI Research Award Innovation Funding for Early Career Researchers
DSA, Deep Learning Indaba , and Artificial Intelligence for Development in Africa , with the support of the International Development Research Centre , are collaborating in the implementation of a research funding initiative on the African continent. Their African AI Research Award Innovation Funding for Early Career Researchers targets Early Career Researchers working on AI-driven projects in Africa.
About the Enterprise Medical Imaging Research Project
The public health sector in Zambia, which primarily provides health services to underserved communities, has a deficit of qualified radiologists, with a report of nine (9) radiologists servicing a population of 18 million individuals, as of 2021 (Bwanga et al., 2021) . This shortfall poses a number of challenges with the requisition, acquisition, and interpretation of medical images. Coupled with this problem is the fact that recent years have seen a rise in the type of medical imaging modalities used in the health sector, including an exponential growth of medical imaging data requiring interpretation.
The scope of work for the DSA-funded project is aimed at implementing machine learning models for the automated classification of medical images.
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 Bwanga, O., Sichone, J. M., Sichone, P. N., & Kazuma, Y. B. (2021). Image interpretation and reporting by radiographers in Africa: findings from the literature review and their application to Zambia. Medical Journal of Zambia, 48(2), 125-135. URL: https://mjz.co.zm/index.php/mjz/article/view/877