Enterprise Medical Imaging in Zambia
The Republic of Zambia, like many countries world-over, is faced with a critical shortage of trained radiologists, medical experts specialised in the interpretation of medical images for radiological diagnosis of health conditions. It was reported that as of 2019, Zambia had only five (5) trained radiologists against a population of 17 million (Bwanga et al., 2019). This project seeks to investigate the challenges resulting from the shortage of radiologists and to investigate the feasibility of implementation of efficient and effective medical imaging workflows using enterprise imaging techniques, in order to demonstrate the potential of enterprise imaging in addressing the grand challenges associated with medical imaging in Zambia.
Project Members
Project Publications
Chibuta, Peter, Lighton Phiri, Ernest Obbie Zulu, and Malaizyo Muzumala. 2026. “Global South Health Practitioners’ Awareness and Perceptions of Integrating Artificial Intelligence in Radiological Workflows: A Quantitative Nationwide Study in Health Facilities in Zambia”. In Medical Image Computing in Resource Constrained Settings, 175-84. Cham, Switzerland: Springer Nature Switzerland. doi:10.1007/978-3-032-13654-1_18. |
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Chileshe, Elijah, and Lighton Phiri. 2026. “Large Scale DICOM Compliance Evaluation of Medical Image Data Elements in Low-Resource Settings”. In Medical Image Computing in Resource Constrained Settings, 279-88. Cham, Switzerland: Springer Nature Switzerland. doi:10.1007/978-3-032-13654-1_28. |
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Muzumala, Malaizyo. 2025. “Exploring Artificial Intelligence Based Interpretation of Medical Images in Radiological Workflows in Zambia”. Department of Computing and Informatics. Lusaka, Zambia: The University of Zambia. |
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Muzumala, Malaizyo, Ernest Obbie Zulu, Peter Chibuta, Mayumbo Nyirenda, and Lighton Phiri. 2025. “Evaluating Perceived Workload, Usability and Usefulness of Artificial Intelligence Systems in Low-Resource Settings: Semi-Automated Classification and Detection of Community Acquired Pneumonia”. In Applications of Medical Artificial Intelligence (AMAI 2024), 116-26. Marrakech, Morocco: Springer Nature Switzerland. doi:10.1007/978-3-031-82007-6_12. |
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Mukuka, Kangwa Emmanuel, Festus Mwape, and Lighton Phiri. 2025. “Enhancing Radiology Workflows: Semi-Automated Cervical Cancer Reporting at the Cancer Diseases Hospital in Zambia”. Lusaka, Zambia: University of Zambia. |
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