A Picture Worth a Thousand Words, Created with One Sentence: Using Artificial Intelligence–created Art to Enhance Medical Education

Huston, John C.; Kaminski, Naftali

doi:10.34197/ats-scholar.2022-0141ps

Cited by 6 publications

(4 citation statements)

References 6 publications

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“…“A picture is worth a thousand words.” [ 39 , 40 ] This study demonstrates the analysis of hospital employee satisfaction through 7 visual diagrams. Hospital accreditations stipulate: “ listening to employees ” voices or establishing a grievance mechanism, conducting employee satisfaction surveys, enhancing communication and interaction, and improving work efficiency .…”

Section: Discussionmentioning

confidence: 94%

Using Rasch Wright map to identify hospital employee satisfaction during and before COVID-19

Chen,

Huang,

Chou

2023

Medicine

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During the surge of the COVID-19 outbreak, medical personnel attended to countless patients, which adversely affected their mental well-being. To support their staff, hospitals implemented guidelines that focused on promoting mental health among medical professionals. The hypothesis that employee satisfaction declined during the COVID-19 pandemic needs confirmation. Several findings were derived from a series of visualizations using Rasch Wright map. The research sample was taken from a medical center in southern Taiwan based on satisfaction survey data from 2017 to 2022 (n = 1222). Perceptions on job satisfaction perceptions during and prior to COVID-19 in 2 stages of 2017 to 2019 and 2020 to 2022 were compared using Rasch Wright map. Through a series of visualizations, including the dimension with the highest satisfaction, the demographical category of hospital employees with the lowest satisfaction during the pandemic, and Rasch Wright map displaying employs’ perfections on 4 domains over years. The results indicated: Employee satisfaction was significantly lower during the COVID-19 period in 2 domains: compensation and benefits, work atmosphere; among the 23 questions, Question 5 (regarding meals provided by the hospital to staff) scored the lowest, while Question 23 (regarding the hospital emergency response and disaster prevention capabilities) scored the highest. Among the 4 domains, organizational leadership had the highest satisfaction; out of 104 demographic variables, 21 groups showed that employee satisfaction during the pandemic was significantly (P < .05) lower than before the pandemic; the selection of specific demographic variables is for top-tier supervisors, and they showed that employee satisfaction during the pandemic was significantly (P < .05) lower than before the pandemic across all 4 dimensions. Therefore, this study accepts the hypothesis that employee satisfaction was negatively affected during the COVID-19 period on 2 domains only: compensation and benefits, work atmosphere. The study visual examination, especially using Rasch Wright map, offers a comparative perspective on hospital staff satisfaction and serves as a methodological guide for subsequent satisfaction research.

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Section: Discussionmentioning

confidence: 94%

Using Rasch Wright map to identify hospital employee satisfaction during and before COVID-19

Chen,

Huang,

Chou

2023

Medicine

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“…AI image generation technology has also been used in 2 distinct studies [ 17 , 18 ]. The first application involved generating images for case-based learning in plastic surgery, for which AI-produced photographs of conditions like skin tumors were used [ 17 ].…”

Section: Resultsmentioning

confidence: 99%

“…The first application involved generating images for case-based learning in plastic surgery, for which AI-produced photographs of conditions like skin tumors were used [ 17 ]. The second study suggested using AI-generated images for reflective exercises within a medical humanities curriculum [ 18 ].…”

Section: Resultsmentioning

confidence: 99%

Opportunities, Challenges, and Future Directions of Generative Artificial Intelligence in Medical Education: Scoping Review

Preiksaitis,

Rose

2023

JMIR Med Educ

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Background Generative artificial intelligence (AI) technologies are increasingly being utilized across various fields, with considerable interest and concern regarding their potential application in medical education. These technologies, such as Chat GPT and Bard, can generate new content and have a wide range of possible applications. Objective This study aimed to synthesize the potential opportunities and limitations of generative AI in medical education. It sought to identify prevalent themes within recent literature regarding potential applications and challenges of generative AI in medical education and use these to guide future areas for exploration. Methods We conducted a scoping review, following the framework by Arksey and O'Malley, of English language articles published from 2022 onward that discussed generative AI in the context of medical education. A literature search was performed using PubMed, Web of Science, and Google Scholar databases. We screened articles for inclusion, extracted data from relevant studies, and completed a quantitative and qualitative synthesis of the data. Results Thematic analysis revealed diverse potential applications for generative AI in medical education, including self-directed learning, simulation scenarios, and writing assistance. However, the literature also highlighted significant challenges, such as issues with academic integrity, data accuracy, and potential detriments to learning. Based on these themes and the current state of the literature, we propose the following 3 key areas for investigation: developing learners’ skills to evaluate AI critically, rethinking assessment methodology, and studying human-AI interactions. Conclusions The integration of generative AI in medical education presents exciting opportunities, alongside considerable challenges. There is a need to develop new skills and competencies related to AI as well as thoughtful, nuanced approaches to examine the growing use of generative AI in medical education.

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“…Generating desired illustrations by utilizing AI to train on data related to human anatomy and various procedures is considered effective in terms of both time and cost. Various efforts involving AI-generated illustrations are being introduced [ 13 , 14 ].…”

Section: To the Editormentioning

confidence: 99%

Necessity of professional medical illustration for increasing the value of the journal

Won,

Yang,

Kim

2023

Korean J Pain

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A Picture Worth a Thousand Words, Created with One Sentence: Using Artificial Intelligence–created Art to Enhance Medical Education

Cited by 6 publications

References 6 publications

Using Rasch Wright map to identify hospital employee satisfaction during and before COVID-19

Using Rasch Wright map to identify hospital employee satisfaction during and before COVID-19

Opportunities, Challenges, and Future Directions of Generative Artificial Intelligence in Medical Education: Scoping Review

Necessity of professional medical illustration for increasing the value of the journal

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