JHEP Reports, Journal Year: 2024, Volume and Issue: 7(1), P. 101266 - 101266
Published: Nov. 14, 2024
Language: Английский
Journal of Educational Evaluation for Health Professions, Journal Year: 2024, Volume and Issue: 21, P. 6 - 6
Published: March 15, 2024
ChatGPT is a large language model (LLM) based on artificial intelligence (AI) capable of responding in multiple languages and generating nuanced highly complex responses. While holds promising applications medical education, its limitations potential risks cannot be ignored.
Language: Английский
Citations
31
Education Sciences, Journal Year: 2024, Volume and Issue: 14(2), P. 172 - 172
Published: Feb. 7, 2024
Many educators and professionals in different industries may need to become more familiar with the basic concepts of artificial intelligence (AI) generative (Gen-AI). Therefore, this paper aims introduce some AI Gen-AI. The approach explanatory is first underlying concepts, such as intelligence, machine learning, deep neural networks, large language models (LLMs), that would allow reader better understand AI. also discusses applications implications on businesses education, followed by current challenges associated
Language: Английский
Citations
30
Advances in healthcare information systems and administration book series, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 19
Published: Feb. 9, 2024
With the increasing popularity of artificial intelligence (AI) applications in medical practices, integration AI technologies into education has garnered significant attention. However, there exists a noticeable research gap when it comes to providing comprehensive guidelines and recommendations for its successful this domain. Addressing is crucial as responsible effective incorporation not only ensures that current future healthcare professionals are well-prepared demands modern medicine but also upholds ethical standards, maximizes potential benefits AI, minimizes risks. The objective chapter fill by offering practical tips actionable insights incorporating education, encompassing practical, ethical, pedagogical, professional implications. Consequently, equips educators learners alike with knowledge tools necessary navigate evolving landscape age AI.
Language: Английский
Citations
28
Interactive Journal of Medical Research, Journal Year: 2024, Volume and Issue: 13, P. e54704 - e54704
Published: Jan. 26, 2024
Background Adherence to evidence-based practice is indispensable in health care. Recently, the utility of generative artificial intelligence (AI) models care has been evaluated extensively. However, lack consensus guidelines on design and reporting findings these studies poses a challenge for interpretation synthesis evidence. Objective This study aimed develop preliminary checklist standardize AI-based education practice. Methods A literature review was conducted Scopus, PubMed, Google Scholar. Published records with “ChatGPT,” “Bing,” or “Bard” title were retrieved. Careful examination methodologies employed included identify common pertinent themes possible gaps reporting. panel discussion held establish unified thorough AI The finalized used evaluate by 2 independent raters. Cohen κ as method interrater reliability. Results final data set that formed basis theme identification analysis comprised total 34 records. 9 collectively referred METRICS (Model, Evaluation, Timing, Range/Randomization, Individual factors, Count, Specificity prompts language). Their details are follows: (1) Model its exact settings; (2) Evaluation approach generated content; (3) Timing testing model; (4) Transparency source; (5) Range tested topics; (6) Randomization selecting queries; (7) factors queries reliability; (8) Count executed test (9) language used. overall mean score 3.0 (SD 0.58). acceptable, range 0.558 0.962 (P<.001 items). With classification per item, highest average recorded “Model” followed “Specificity” while lowest scores “Randomization” item (classified suboptimal) “Individual factors” satisfactory). Conclusions can facilitate guiding researchers toward best practices results. highlight need standardized algorithms care, considering variability observed proposed could be helpful base universally accepted which swiftly evolving research topic.
Language: Английский
Citations
23
International Journal of Nursing Studies, Journal Year: 2024, Volume and Issue: 153, P. 104717 - 104717
Published: Feb. 8, 2024
Language: Английский
Citations
19
Radiography, Journal Year: 2024, Volume and Issue: 30(3), P. 737 - 744
Published: Feb. 29, 2024
IntroductionThe healthcare sector invests significantly in communication skills training, but not always with satisfactory results. Recently, generative Large Language Models, have shown promising results medical education. This study aims to use ChatGPT simulate radiographer-patient conversations about the critical moment of claustrophobia management during MRI, exploring how Artificial Intelligence can improve radiographers' skills.MethodsThis exploits specifically designed prompts on ChatGPT-3.5 and ChatGPT-4 generate simulated between virtual claustrophobic patients six radiographers varying levels work experience focusing their differences model size language generation capabilities. Success rates responses were analysed. The methods convincing undergo MRI despite also evaluated.ResultsA total 60 simulations conducted, achieving a success rate 96.7% (58/60). exhibited errors 40% (12/30) simulations, while showed no errors.In terms out 164 responses, 70.2% (115/164) categorized as "Supportive Instructions," followed by "Music Therapy" at 18.3% (30/164). Experts mainly used Instructions" (82.2%, 51/62) "Breathing Techniques" (9.7%, 6/62). Intermediate participants favoured (26%, 13/50), Beginner frequently utilized "Mild Sedation" (15.4%, 8/52).ConclusionThe simulation clinical scenarios via proves valuable assessing testing skills, especially managing MRI. pilot highlights potential preclinical recognizing different training needs professional experience.Implications for practiceThis is relevant radiography practice, where AI increasingly widespread, it explores new way radiographers.
Language: Английский
Citations
4
European Journal of Education, Journal Year: 2025, Volume and Issue: 60(1)
Published: Feb. 14, 2025
ABSTRACT This systematic review investigates the impact of generative artificial intelligence (GenAI) tools on developing academic skills in higher education. Analysing 158 studies published between 2021 and 2024, it focuses GenAI development cognitive, technical interpersonal skills. The results reveal that 94% sampled reported significant improvements cognitive skills, like critical thinking, problem‐solving, analytical metacognitive abilities, facilitated by personalised learning feedback. Indeed, was research (24%), writing (26%), data analysis (33%) literacy (18%). Additionally, were found to promote fostering interactive engaging environments, with notable communication organisation empathy (5%) teamwork (45%). Hence, this underscores importance ethical responsible use tools, ongoing monitoring active stakeholder engagement maximise their benefits They offer a promising avenue for advancement enhancing proficiency promoting effective teamwork. Therefore, significantly enhance skills; however, integration requires robust framework sustained examination long‐term impacts.
Language: Английский
Citations
0
Published: Jan. 1, 2025
Language: Английский
Citations
0
World Journal of Clinical Cases, Journal Year: 2025, Volume and Issue: 13(19)
Published: March 18, 2025
Cardiac rehabilitation is a crucial multidisciplinary approach to improve patient outcomes. There growing body of evidence that suggests these programs contribute towards reducing cardiovascular mortality and recurrence. Despite this, cardiac underutilized adherence has been demonstrated barrier in achieving As result, there focus on innovating programs, especially from the standpoint digital health personalized medicine. This editorial discusses possible roles large language models, such as their role ChatGPT, further personalizing through simplifying medical jargon employing motivational interviewing techniques, thus boosting engagement adherence. However, possibilities must be investigated clinical literature. Likewise, integration models will challenging its nascent stages ensure accurate ethical information delivery.
Language: Английский
Citations
0
Frontiers in Education, Journal Year: 2025, Volume and Issue: 10
Published: March 26, 2025
Citations
0