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Congress: ECR25
Poster Number: C-17668
Type: Poster: EPOS Radiologist (scientific)
DOI: 10.26044/ecr2025/C-17668
Authorblock: N. Stogiannos1, M. Jennings2, C. St George2, J. Culbertson2, H. Salehi3, S. Furterer4, M. B. Pergola2, M. Culp2, C. Malamateniou1; 1London/UK, 2Albuquerque, NM/US, 3Dayton, OH/US, 4Columbus, OH/US
Disclosures:
Nikolaos Stogiannos: Nothing to disclose
Michael Jennings: Nothing to disclose
Craig St George: Nothing to disclose
John Culbertson: Nothing to disclose
Hugh Salehi: Nothing to disclose
Sandra Furterer: Nothing to disclose
Melissa Bristle Pergola: Nothing to disclose
Melissa Culp: Nothing to disclose
Christina Malamateniou: Nothing to disclose
Keywords: Artificial Intelligence, CAD, Education, Education and training
Purpose Artificial Intelligence (AI) has already started to transform many sectors of the medical imaging workforce, and its use in healthcare is promising, since it can harness digital data to enhance patient experience and improve the existing clinical workflows [1]. There has been an exponential increase in the usage and diversity of accredited AI-enabled clinical applications in medical imaging and radiotherapy [2]. This has resulted, in most cases, in improved efficiency and efficacy. The medical radiation technologists’ (MRTs) profession, known as...
Read more Methods and materials An online survey was built in Checkbox, version 8.3.0 (Checkbox Technology, Inc., San Francisco). The survey questions were based on previously implemented surveys on AI [7,8], with input from AI experts in medical imaging and radiotherapy. The ASRT research department provided further guidance on survey questions and structure, with support from the ASRT senior executive and leadership team.The survey consisted of 37 total questions: 7 demographic questions, 26 closed-type questions related to AI, and 4 open-ended questions that allowed respondents...
Read more Results Out of 5,066 educators, a total of 373 valid responses were received, which yielded a response rate of 7.4%. The geographical distribution of the responses across the States can be seen below. [fig 1] Respondents were also asked to indicate their level of agreement with the statement, ‘’I have appropriate training to learn and apply new technology, including AI/ML automation”. The responses are summarised below. A 22% of the respondents answered this question favourably (strongly agree and agree), while 49% answered the question...
Read more Conclusion Most educators in the U.S.A were familiar with the concept of AI. However, improvements should be made to integrate AI in academic curricula. Educators should ensure the ethical use of AI tools in education and provide students with the necessary knowledge on how to use these frameworks to improve patient experiences and outcomes. AI training, funding, and provision of resources were highlighted as priorities by educators. The results of this study strengthen the argument for interprofessional collaboration to create successful,...
Read more References 1. Stogiannos N, O'Regan T, Scurr E, Litosseliti L, Pogose M, Harvey H, Kumar A, Malik R, Barnes A, McEntee MF, Malamateniou C. AI implementation in the UK landscape: Knowledge of AI governance, perceived challenges and opportunities, and ways forward for radiographers. Radiography (Lond) 2024;30(2):612-621. https://doi.org/10.1016/j.radi.2024.01.019 2. Mello-Thoms C, Mello CAB. Clinical applications of artificial intelligence in radiology. Br J Radiol 2023;96(1150):20221031. https://doi.org/10.1259/bjr.20221031 3. van Leeuwen KG, de Rooij M, Schalekamp S, van Ginneken B, Rutten MJCM. How does artificial intelligence in...
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