Enhancing medical imaging education: integrating computing technologies, digital image processing and artificial intelligence DOI Creative Commons
Sibusiso Mdletshe, Alan Wang

Journal of Medical Radiation Sciences, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 7, 2024

The rapid advancement of technology has brought significant changes to various fields, including medical imaging (MI). This discussion paper explores the integration computing technologies (e.g. Python and MATLAB), digital image processing enhancement, segmentation three-dimensional reconstruction) artificial intelligence (AI) into undergraduate MI curriculum. By examining current educational practices, gaps limitations that hinder development future-ready professionals are identified. A comprehensive curriculum framework is proposed, incorporating essential computational skills, advanced techniques state-of-the-art AI tools, such as large language models like ChatGPT. proposed aims improve quality education significantly better equip students for future professional practice challenges while enhancing diagnostic accuracy, improving workflow efficiency preparing evolving demands field.

Язык: Английский

Ethical AI: a qualitative study exploring ethical challenges and solutions on the use of AI in medical imaging DOI Creative Commons
Nikolaos Stogiannos, Eleni Georgiadou,

Nikoleta Rarri

и другие.

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

1

R-AI-diographers: a European survey on perceived impact of AI on professional identity, careers, and radiographers’ roles DOI Creative Commons
Nikolaos Stogiannos, G. Walsh, Benard Ohene Botwe

и другие.

Insights into Imaging, Год журнала: 2025, Номер 16(1)

Опубликована: Фев. 17, 2025

Abstract Objectives Radiographers use advanced medical imaging and radiotherapy (MIRT) equipment. They are also a digitally mature resilient workforce in healthcare. Artificial intelligence is already changing their clinical practice roles data acquisition, post-processing, workflow management. It therefore vital to understand the impact of AI on careers, professional identity radiographers, as key stakeholders digital transformation healthcare within ecosystem. Methods A European radiographer survey, endorsed by Federation Radiographer Societies (EFRS), was distributed online. piloted with twelve radiographers translated into eight languages. Although this study included both qualitative quantitative results, paper emphasises aspect. Results total 2206 have responded from 37 different countries. Despite some concerns around deskilling, future identity, job prospects, participants showed overall optimistic views about This particularly strong for those prior education (mean: 2.15 vs. 1.89; p -value: < 0.001), hands-on experience (correlation: 0.047; 0.038), countries higher literacy 2.00 vs.1.93; 0.027) academic level radiography 3.28 3.15; 0.002). Men appeared slightly more enthused development technological skills women honing patient-centred care skills. Finally, interprofessional collaboration seen essential not only seamless integration but supporting patient benefit. Conclusion While implementation advances, needs keep at pace ensure acceptability, trust, safe technology professionals, minimising role changes enabling them see opportunities service transformation. Critical relevance statement aims map out perceived careers radiographers. Key Points impacting radiographers’ identity. increasing awareness, still lacking across Europe. acceptability trust which facilitates Graphical

Язык: Английский

Процитировано

0

Evaluation of a customised, AI-focused educational seminar delivered to final year undergraduate radiography students in the UK: A cross-sectional study DOI Creative Commons
Nikolaos Stogiannos, Emily Skelton,

Sri Kumar

и другие.

Radiography, Год журнала: 2025, Номер 31(3), С. 102926 - 102926

Опубликована: Март 29, 2025

AI education is essential to facilitate seamless clinical integration. The HCPC in the UK requires all radiographers have some level of digital skills maintain safety practice. This study aimed evaluate impact a dedicated seminar on radiography students. A 1.5-h in-person was delivered by an vendor final year undergraduate diagnostic students at University. course consisted both theory and practice training. An online survey built piloted, consisting closed open-ended questions, explore their knowledge, confidence AI, before (pre-test) after delivery (post-test) using 10-point scale. Pre-test distributed two weeks post-test open after. total 68 answered pre-test 31 survey. Students' theoretical knowledge (Mean = 6.57 vs Mean 3.85), 5.39 3.44) 5.47 3.43) were significantly improved seminar. Their responses became more focused specific In surveys expressed concerns around reliability accountability data management security, patient confidentiality overreliance technology questions. They also requested training with hands-on options degree. confirms importance even brief, but customised educational interventions relating for radiographers. learning needs be maximise retention applicability include practical aspects consolidation skills. These findings will help educators build focused, tailored courses future

Язык: Английский

Процитировано

0

Artificial intelligence in higher education institutions: review of innovations, opportunities and challenges DOI Creative Commons

Samuel Ocen,

Joseph Elasu, Sylvia Manjeri Aarakit

и другие.

Frontiers in Education, Год журнала: 2025, Номер 10

Опубликована: Март 3, 2025

Artificial intelligence is revolutionizing industries including institutions of higher learning as it enhances teaching and processes, streamline administrative tasks drive innovations. Despite the unprecedented opportunities, AI tools if not used correctly, can be challenging in education institutions. The purpose this study was to comprehensively review innovations, opportunities challenges associated with use Education learning. A systematic literature methodology adopted locate select existing studies, analyze synthesize evidence arrive at clear conclusion about current debate area study. Following PRISMA, analyzed a total 54 documents that met inclusion exclusion criteria set for selection documents. unveiled many enhanced research capabilities, automation among others. Intelligence are found refine different units include ethical concerns, integrity issues data fabrication issues. With notwithstanding, benefits cannot over emphasized. remains powerful tool research, tasked, personalized learning, inclusivity accessibility educational content all. Emphasis should put regulatory frameworks detailing how such while maintaining level standards required.

Язык: Английский

Процитировано

0

Lessons on AI implementation from senior clinical practitioners: An exploratory qualitative study in medical imaging and radiotherapy in the UK DOI Creative Commons
Nikolaos Stogiannos, Tracy O’Regan,

Erica Scurr

и другие.

Journal of medical imaging and radiation sciences, Год журнала: 2024, Номер 56(1), С. 101797 - 101797

Опубликована: Ноя. 22, 2024

Язык: Английский

Процитировано

1

Enhancing medical imaging education: integrating computing technologies, digital image processing and artificial intelligence DOI Creative Commons
Sibusiso Mdletshe, Alan Wang

Journal of Medical Radiation Sciences, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 7, 2024

The rapid advancement of technology has brought significant changes to various fields, including medical imaging (MI). This discussion paper explores the integration computing technologies (e.g. Python and MATLAB), digital image processing enhancement, segmentation three-dimensional reconstruction) artificial intelligence (AI) into undergraduate MI curriculum. By examining current educational practices, gaps limitations that hinder development future-ready professionals are identified. A comprehensive curriculum framework is proposed, incorporating essential computational skills, advanced techniques state-of-the-art AI tools, such as large language models like ChatGPT. proposed aims improve quality education significantly better equip students for future professional practice challenges while enhancing diagnostic accuracy, improving workflow efficiency preparing evolving demands field.

Язык: Английский

Процитировано

0