MIRERC 046/2025: Knowledge, Attitudes, and Practices of Radiologists and Radiology Residents in Kenya on the Use of Artificial Intelligence for Breast Cancer Screening

Abstract

Background
While Artificial Intelligence (AI) offers potential solutions to radiologist shortages and diagnostic challenges, its adoption is met with mixed reactions by key stakeholders, most often skepticism.
Objective
This study examines the knowledge, attitudes, and practices (KAP) of radiologists and radiology residents in Kenya regarding Artificial Intelligence (AI) in breast cancer imaging, particularly in screening mammography.
Methodology
Using a mixed-methods, cross-sectional design, data will be collected from radiologists and radiology residents nationally via structured surveys and key informant interviews (KIIs). Quantitative data will undergo descriptive and inferential analysis, while thematic analysis will extract qualitative insights. The findings will inform collaboration between Machine Learning (ML) engineers and radiologists towards adoption of safe, effective AI tools that augment radiologists’ breast cancer screening workflows.
Utility of the study
The findings will also inform policy recommendations and integration strategies, supporting early breast cancer detection through scaled-up screening programs in Kenya.