Perspectives of radiologists in Ghana about the emerging role of artificial intelligence in radiologyKey points
Background: The integration of Artificial Intelligence (AI)-based technologies in medicine is advancing rapidly especially in the field of radiology. This however, is at a slow pace in Africa, hence, this study to evaluate the perspectives of Ghanaian radiologists. Methods: Data for this cross-secti...
| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-05-01
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| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844023027652 |
| _version_ | 1827937530083803136 |
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| author | Emmanuel Kobina Mesi Edzie Klenam Dzefi-Tettey Abdul Raman Asemah Edmund Kwakye Brakohiapa Samuel Asiamah Frank Quarshie Adu Tutu Amankwa Amrit Raj Obed Nimo Evans Boadi Joshua Mensah Kpobi Richard Ato Edzie Bernard Osei Veronica Turkson Henry Kusodzi |
| author_facet | Emmanuel Kobina Mesi Edzie Klenam Dzefi-Tettey Abdul Raman Asemah Edmund Kwakye Brakohiapa Samuel Asiamah Frank Quarshie Adu Tutu Amankwa Amrit Raj Obed Nimo Evans Boadi Joshua Mensah Kpobi Richard Ato Edzie Bernard Osei Veronica Turkson Henry Kusodzi |
| author_sort | Emmanuel Kobina Mesi Edzie |
| collection | DOAJ |
| description | Background: The integration of Artificial Intelligence (AI)-based technologies in medicine is advancing rapidly especially in the field of radiology. This however, is at a slow pace in Africa, hence, this study to evaluate the perspectives of Ghanaian radiologists. Methods: Data for this cross-sectional prospective study was collected between September and November 2021 through an online survey and entered into SPSS for analysis. A Mann–Whitney U test assisted in checking for possible gender differences in the mean Likert scale responses on the radiologists’ perspectives about AI in radiology. Statistical significance was set at P ≤ 0.05. Results: The study comprised 77 radiologists, with more males (71.4%). 97.4% were aware of the concept of AI, with their initial exposure via conferences (42.9%). The majority of the respondents had average awareness (36.4%) and below average expertise (44.2%) in radiological AI usage. Most of the participants (54.5%) stated, they do not use AI in their practices. The respondents disagreed that AI will ultimately replace radiologists in the near future (average Likert score = 3.49, SD = 1.096) and that AI should be an integral part of the training of radiologists (average Likert score = 1.91, SD = 0.830). Conclusion: Although the radiologists had positive opinions about the capabilities of AI, they exhibited an average awareness of and below average expertise in the usage of AI applications in radiology. They agreed on the potential life changing impact of AI and were of the view that AI will not replace radiologists but serve as a complement. There was inadequate radiological AI infrastructure in Ghana. |
| first_indexed | 2024-03-13T08:27:04Z |
| format | Article |
| id | doaj.art-af52d4d395d14dfeb0f8dfd08059b3bc |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-03-13T08:27:04Z |
| publishDate | 2023-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-af52d4d395d14dfeb0f8dfd08059b3bc2023-05-31T04:44:46ZengElsevierHeliyon2405-84402023-05-0195e15558Perspectives of radiologists in Ghana about the emerging role of artificial intelligence in radiologyKey pointsEmmanuel Kobina Mesi Edzie0Klenam Dzefi-Tettey1Abdul Raman Asemah2Edmund Kwakye Brakohiapa3Samuel Asiamah4Frank Quarshie5Adu Tutu Amankwa6Amrit Raj7Obed Nimo8Evans Boadi9Joshua Mensah Kpobi10Richard Ato Edzie11Bernard Osei12Veronica Turkson13Henry Kusodzi14Department of Medical Imaging, School of Medical Sciences, College of Health and Allied Sciences, University of Cape Coast, Cape Coast, Ghana; Corresponding author.Department of Radiology, Korle Bu Teaching Hospital, 1 Guggisberg Avenue, Accra, GhanaDepartment of Medical Imaging, School of Medical Sciences, College of Health and Allied Sciences, University of Cape Coast, Cape Coast, GhanaDepartment of Radiology, University of Ghana Medical School, Accra, GhanaDepartment of Radiology, Korle Bu Teaching Hospital, 1 Guggisberg Avenue, Accra, GhanaAfrican Institute for Mathematical Sciences (AIMS), Summerhill Estate, East Legon Hills, Santoe, Accra, GhanaDepartment of Radiology, School of Medical Sciences, College of Health Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, GhanaDepartment of Pediatrics, School of Medical Sciences, College of Health and Allied Sciences, University of Cape Coast, Cape Coast, GhanaDepartment of Imaging Technology and Sonography, College of Health and Allied Sciences, University of Cape Coast, Cape Coast, GhanaDepartment of Radiology, Korle Bu Teaching Hospital, 1 Guggisberg Avenue, Accra, GhanaDepartment of Radiology, Korle Bu Teaching Hospital, 1 Guggisberg Avenue, Accra, GhanaDepartment of Medical Imaging, School of Medical Sciences, College of Health and Allied Sciences, University of Cape Coast, Cape Coast, GhanaAfrican Institute for Mathematical Sciences (AIMS), Summerhill Estate, East Legon Hills, Santoe, Accra, GhanaDepartment of Medical Imaging, School of Medical Sciences, College of Health and Allied Sciences, University of Cape Coast, Cape Coast, GhanaDepartment of Medical Imaging, School of Medical Sciences, College of Health and Allied Sciences, University of Cape Coast, Cape Coast, GhanaBackground: The integration of Artificial Intelligence (AI)-based technologies in medicine is advancing rapidly especially in the field of radiology. This however, is at a slow pace in Africa, hence, this study to evaluate the perspectives of Ghanaian radiologists. Methods: Data for this cross-sectional prospective study was collected between September and November 2021 through an online survey and entered into SPSS for analysis. A Mann–Whitney U test assisted in checking for possible gender differences in the mean Likert scale responses on the radiologists’ perspectives about AI in radiology. Statistical significance was set at P ≤ 0.05. Results: The study comprised 77 radiologists, with more males (71.4%). 97.4% were aware of the concept of AI, with their initial exposure via conferences (42.9%). The majority of the respondents had average awareness (36.4%) and below average expertise (44.2%) in radiological AI usage. Most of the participants (54.5%) stated, they do not use AI in their practices. The respondents disagreed that AI will ultimately replace radiologists in the near future (average Likert score = 3.49, SD = 1.096) and that AI should be an integral part of the training of radiologists (average Likert score = 1.91, SD = 0.830). Conclusion: Although the radiologists had positive opinions about the capabilities of AI, they exhibited an average awareness of and below average expertise in the usage of AI applications in radiology. They agreed on the potential life changing impact of AI and were of the view that AI will not replace radiologists but serve as a complement. There was inadequate radiological AI infrastructure in Ghana.http://www.sciencedirect.com/science/article/pii/S2405844023027652Artificial intelligencePerceptionMachine learningRadiologyGhana |
| spellingShingle | Emmanuel Kobina Mesi Edzie Klenam Dzefi-Tettey Abdul Raman Asemah Edmund Kwakye Brakohiapa Samuel Asiamah Frank Quarshie Adu Tutu Amankwa Amrit Raj Obed Nimo Evans Boadi Joshua Mensah Kpobi Richard Ato Edzie Bernard Osei Veronica Turkson Henry Kusodzi Perspectives of radiologists in Ghana about the emerging role of artificial intelligence in radiologyKey points Heliyon Artificial intelligence Perception Machine learning Radiology Ghana |
| title | Perspectives of radiologists in Ghana about the emerging role of artificial intelligence in radiologyKey points |
| title_full | Perspectives of radiologists in Ghana about the emerging role of artificial intelligence in radiologyKey points |
| title_fullStr | Perspectives of radiologists in Ghana about the emerging role of artificial intelligence in radiologyKey points |
| title_full_unstemmed | Perspectives of radiologists in Ghana about the emerging role of artificial intelligence in radiologyKey points |
| title_short | Perspectives of radiologists in Ghana about the emerging role of artificial intelligence in radiologyKey points |
| title_sort | perspectives of radiologists in ghana about the emerging role of artificial intelligence in radiologykey points |
| topic | Artificial intelligence Perception Machine learning Radiology Ghana |
| url | http://www.sciencedirect.com/science/article/pii/S2405844023027652 |
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