Radiographers' Acceptance on the Integration of Artificial Intelligence into Medical Imaging Practice

被引:0
|
作者
Sharip, Hairenanorashikin [1 ]
Zakaria, Wan Farah Wahida Che [1 ]
Sam, Leong Sook [1 ]
Masoud, Maida Ali [2 ]
Junaidi, Mohamad Zafran Hakim Mohd [1 ]
机构
[1] Univ Teknol MARA UITM, Fac Hlth Sci, Shah Alam, Malaysia
[2] Mnazi Mmoja Hosp, Kaunda Rd, Zanzibar, Tanzania
来源
关键词
Artificial Intelligence (AI); Radiographer; Knowledge and Attitude; Job Security;
D O I
10.21834/e-bpj.v8i25.4872
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Artificial intelligence (AI) integration in medical imaging is a promising field for enhancing patient care, performance, and efficiency. Radiographers, on the other hand, are concerned about AI's acceptance and potential to replace them. This study assessed radiographers' acceptance of AI integration by considering their knowledge, attitudes, and job security. Based on demographic characteristics, there were no significant differences in knowledge, attitude, or job security level. Completing AI training, on the other hand, had a considerable influence. Overall, radiographers have a good level of knowledge and are enthusiastic about using AI tools into their regular activities.
引用
收藏
页码:255 / 260
页数:6
相关论文
共 50 条
  • [1] The integration of artificial intelligence in medical imaging practice: Perspectives of African radiographers
    Botwe, B. O.
    Akudjedu, T. N.
    Antwi, W. K.
    Rockson, P.
    Mkoloma, S. S.
    Balogun, E. O.
    Elshami, W.
    Bwambale, J.
    Barare, C.
    Mdletshe, S.
    Yao, B.
    Arkoh, S.
    [J]. RADIOGRAPHY, 2021, 27 (03) : 861 - 866
  • [2] Radiographers? knowledge, attitudes and expectations of artificial intelligence in medical imaging
    Coakley, S.
    Young, R.
    Moore, N.
    England, A.
    O'Mahony, A.
    O'Connor, O. J.
    Maher, M.
    McEntee, M. F.
    [J]. RADIOGRAPHY, 2022, 28 (04) : 943 - 948
  • [3] Artificial intelligence in medical imaging practice in Africa: a qualitative content analysis study of radiographers’ perspectives
    William Kwadwo Antwi
    Theophilus N. Akudjedu
    Benard Ohene Botwe
    [J]. Insights into Imaging, 12
  • [4] Artificial intelligence in medical imaging practice in Africa: a qualitative content analysis study of radiographers' perspectives
    Antwi, William Kwadwo
    Akudjedu, Theophilus N.
    Botwe, Benard Ohene
    [J]. INSIGHTS INTO IMAGING, 2021, 12 (01)
  • [5] Radiologists' and Radiographers' Perspectives on Artificial Intelligence in Medical Imaging in Saudi Arabia
    Alyami, Ali S.
    Majrashi, Naif A.
    Shubayr, Nasser A.
    [J]. CURRENT MEDICAL IMAGING, 2024, 20
  • [6] Assessment of the Willingness of Radiologists and Radiographers to Accept the Integration of Artificial Intelligence Into Radiology Practice
    Abuzaid, Mohamed M.
    Elshami, Wiam
    Tekin, Huseyin
    Issa, Bashar
    [J]. ACADEMIC RADIOLOGY, 2022, 29 (01) : 87 - 94
  • [7] Radiographers' perspectives on the emerging integration of artificial intelligence into diagnostic imaging: The Ghana study
    Botwe, Benard O.
    Antwi, William K.
    Arkoh, Samuel
    Akudjedu, Theophilus N.
    [J]. JOURNAL OF MEDICAL RADIATION SCIENCES, 2021, 68 (03) : 260 - 268
  • [8] An extensive survey of radiographers from the Middle East and India on artificial intelligence integration in radiology practice
    Abuzaid, Mohamed M.
    Elshami, Wiam
    McConnell, Jonathan
    Tekin, H. O.
    [J]. HEALTH AND TECHNOLOGY, 2021, 11 (05) : 1045 - 1050
  • [9] An extensive survey of radiographers from the Middle East and India on artificial intelligence integration in radiology practice
    Mohamed M. Abuzaid
    Wiam Elshami
    Jonathan McConnell
    H. O. Tekin
    [J]. Health and Technology, 2021, 11 : 1045 - 1050
  • [10] Artificial Intelligence in medical imaging practice: looking to the future
    Lewis, Sarah J.
    Gandomkar, Ziba
    Brennan, Patrick C.
    [J]. JOURNAL OF MEDICAL RADIATION SCIENCES, 2019, 66 (04) : 292 - 295