Knowledge, perceptions, and interest of referring physicians regarding the implementation of Artificial Intelligence in CT Imaging in the Democratic Republic of Congo

Introduction Artificial intelligence (AI) is increasingly integrated into medical imaging, including computed tomography (CT); however, its uptake remains limited in low-resource settings such as the Democratic Republic of Congo (DRC). Understanding physicians’ knowledge, perceptions, and inter...

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Main Authors: Tacite Kpanya Mazoba, Benjamin Bofengu Lombo, Gertrude Mvila Luyeye, Jean Tshibola Mukaya, Antoine Aundu Molua
Format: Article
Language:English
Published: Orapuh, Inc. 2025-06-01
Series:Orapuh Journal
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Online Access:https://www.orapuh.org/ojs/ojs-3.1.2-4/index.php/orapj/article/view/428
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author Tacite Kpanya Mazoba
Benjamin Bofengu Lombo
Gertrude Mvila Luyeye
Jean Tshibola Mukaya
Antoine Aundu Molua
author_facet Tacite Kpanya Mazoba
Benjamin Bofengu Lombo
Gertrude Mvila Luyeye
Jean Tshibola Mukaya
Antoine Aundu Molua
author_sort Tacite Kpanya Mazoba
collection DOAJ
description Introduction Artificial intelligence (AI) is increasingly integrated into medical imaging, including computed tomography (CT); however, its uptake remains limited in low-resource settings such as the Democratic Republic of Congo (DRC). Understanding physicians’ knowledge, perceptions, and interest is essential for guiding effective implementation strategies. Purpose To assess levels of knowledge, perception, and interest regarding AI integration in CT imaging among physicians in the DRC, and to identify relevant demographic and professional correlates. Methods A cross-sectional electronic survey was conducted between September and December 2024 among 740 physicians across the DRC. The questionnaire captured sociodemographic information and assessed AI-related knowledge (using a scored set of objective items, with ≥50% considered acceptable), perception, and interest (using 5-point Likert scales). Bivariate analyses (Chi-square and t-tests) and multivariate logistic regressions were used to identify predictors of high knowledge, favourable perception, and strong interest. Results Among participants, 64.9% were aged 35 years or younger, 67.6% were male, 70.9% practised in Kinshasa, and 65.1% were general practitioners. Acceptable knowledge was observed in 54.7% of respondents. Favourable perception and strong interest were reported by 46.2% and 66.8% of respondents, respectively. In adjusted analyses, being under 36 years, having ≤15 years of professional experience, working as a general practitioner, and practising in a provincial setting were significantly associated with higher levels of knowledge, perception, or interest (p < .05). Conclusion Early-career physicians, general practitioners, and those practising outside the capital appear more receptive to AI in CT imaging. These findings highlight the importance of targeted training initiatives and policy engagement to promote equitable and effective AI integration in medical imaging across the DRC.
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spelling doaj-art-0726189d40d040e1998c75201f4d7fc02025-08-20T02:36:44ZengOrapuh, Inc.Orapuh Journal2644-37402025-06-016610.4314/orapj.v6i6.58Knowledge, perceptions, and interest of referring physicians regarding the implementation of Artificial Intelligence in CT Imaging in the Democratic Republic of CongoTacite Kpanya Mazoba0Benjamin Bofengu Lombo1Gertrude Mvila Luyeye2Jean Tshibola Mukaya3Antoine Aundu Molua4University of Kinshasa, Kinshasa, XI, Democratic Republic of the CongoUniversity of Kinshasa, Kinshasa, XI, Democratic Republic of the CongoUniversity of Kinshasa, Kinshasa, XI, Democratic Republic of the CongoUniversity of Kinshasa, Kinshasa, XI, Democratic Republic of the CongoUniversity of Kinshasa, Kinshasa, XI, Democratic Republic of the Congo Introduction Artificial intelligence (AI) is increasingly integrated into medical imaging, including computed tomography (CT); however, its uptake remains limited in low-resource settings such as the Democratic Republic of Congo (DRC). Understanding physicians’ knowledge, perceptions, and interest is essential for guiding effective implementation strategies. Purpose To assess levels of knowledge, perception, and interest regarding AI integration in CT imaging among physicians in the DRC, and to identify relevant demographic and professional correlates. Methods A cross-sectional electronic survey was conducted between September and December 2024 among 740 physicians across the DRC. The questionnaire captured sociodemographic information and assessed AI-related knowledge (using a scored set of objective items, with ≥50% considered acceptable), perception, and interest (using 5-point Likert scales). Bivariate analyses (Chi-square and t-tests) and multivariate logistic regressions were used to identify predictors of high knowledge, favourable perception, and strong interest. Results Among participants, 64.9% were aged 35 years or younger, 67.6% were male, 70.9% practised in Kinshasa, and 65.1% were general practitioners. Acceptable knowledge was observed in 54.7% of respondents. Favourable perception and strong interest were reported by 46.2% and 66.8% of respondents, respectively. In adjusted analyses, being under 36 years, having ≤15 years of professional experience, working as a general practitioner, and practising in a provincial setting were significantly associated with higher levels of knowledge, perception, or interest (p < .05). Conclusion Early-career physicians, general practitioners, and those practising outside the capital appear more receptive to AI in CT imaging. These findings highlight the importance of targeted training initiatives and policy engagement to promote equitable and effective AI integration in medical imaging across the DRC. https://www.orapuh.org/ojs/ojs-3.1.2-4/index.php/orapj/article/view/428Artificial Intelligencecomputed tomographymedical imagingknowledgeperceptioninterest
spellingShingle Tacite Kpanya Mazoba
Benjamin Bofengu Lombo
Gertrude Mvila Luyeye
Jean Tshibola Mukaya
Antoine Aundu Molua
Knowledge, perceptions, and interest of referring physicians regarding the implementation of Artificial Intelligence in CT Imaging in the Democratic Republic of Congo
Orapuh Journal
Artificial Intelligence
computed tomography
medical imaging
knowledge
perception
interest
title Knowledge, perceptions, and interest of referring physicians regarding the implementation of Artificial Intelligence in CT Imaging in the Democratic Republic of Congo
title_full Knowledge, perceptions, and interest of referring physicians regarding the implementation of Artificial Intelligence in CT Imaging in the Democratic Republic of Congo
title_fullStr Knowledge, perceptions, and interest of referring physicians regarding the implementation of Artificial Intelligence in CT Imaging in the Democratic Republic of Congo
title_full_unstemmed Knowledge, perceptions, and interest of referring physicians regarding the implementation of Artificial Intelligence in CT Imaging in the Democratic Republic of Congo
title_short Knowledge, perceptions, and interest of referring physicians regarding the implementation of Artificial Intelligence in CT Imaging in the Democratic Republic of Congo
title_sort knowledge perceptions and interest of referring physicians regarding the implementation of artificial intelligence in ct imaging in the democratic republic of congo
topic Artificial Intelligence
computed tomography
medical imaging
knowledge
perception
interest
url https://www.orapuh.org/ojs/ojs-3.1.2-4/index.php/orapj/article/view/428
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