Artificial Intelligence Revolutionizing the Field of Medical Education

Narayanan, Suresh; Ramakrishnan, Rajprasath; Durairaj, Elantamilan; Das, Arghya

doi:10.7759/cureus.49604

Cited by 2 publications

(1 citation statement)

References 47 publications

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“…The utilization of unique educational methods could help overcome this challenge since the study participants indicated that workshops, collaborative activities, scientific conferences, and extracurricular activities were their favorite learning types. These would be simpler to apply in a complex medical curriculum and more agreeable to medical students [ 66 ]. Although some participants expressed concern that a lack of mathematical or computer science understanding would limit effective learning about AI, the rest did not believe that technical knowledge would be a challenge to the understanding of AI.…”

Section: Discussionmentioning

confidence: 99%

Perceptions of undergraduate medical students on artificial intelligence in medicine: mixed-methods survey study from Palestine

Jebreen,

Radwan,

Kammoun-Rebai

et al. 2024

BMC Med Educ

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Background The current applications of artificial intelligence (AI) in medicine continue to attract the attention of medical students. This study aimed to identify undergraduate medical students’ attitudes toward AI in medicine, explore present AI-related training opportunities, investigate the need for AI inclusion in medical curricula, and determine preferred methods for teaching AI curricula. Methods This study uses a mixed-method cross-sectional design, including a quantitative study and a qualitative study, targeting Palestinian undergraduate medical students in the academic year 2022–2023. In the quantitative part, we recruited a convenience sample of undergraduate medical students from universities in Palestine from June 15, 2022, to May 30, 2023. We collected data by using an online, well-structured, and self-administered questionnaire with 49 items. In the qualitative part, 15 undergraduate medical students were interviewed by trained researchers. Descriptive statistics and an inductive content analysis approach were used to analyze quantitative and qualitative data, respectively. Results From a total of 371 invitations sent, 362 responses were received (response rate = 97.5%), and 349 were included in the analysis. The mean age of participants was 20.38 ± 1.97, with 40.11% (140) in their second year of medical school. Most participants (268, 76.79%) did not receive formal education on AI before or during medical study. About two-thirds of students strongly agreed or agreed that AI would become common in the future (67.9%, 237) and would revolutionize medical fields (68.7%, 240). Participants stated that they had not previously acquired training in the use of AI in medicine during formal medical education (260, 74.5%), confirming a dire need to include AI training in medical curricula (247, 70.8%). Most participants (264, 75.7%) think that learning opportunities for AI in medicine have not been adequate; therefore, it is very important to study more about employing AI in medicine (228, 65.3%). Male students (3.15 ± 0.87) had higher perception scores than female students (2.81 ± 0.86) (p < 0.001). The main themes that resulted from the qualitative analysis of the interview questions were an absence of AI learning opportunities, the necessity of including AI in medical curricula, optimism towards the future of AI in medicine, and expected challenges related to AI in medical fields. Conclusion Medical students lack access to educational opportunities for AI in medicine; therefore, AI should be included in formal medical curricula in Palestine.

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Section: Discussionmentioning

confidence: 99%

Perceptions of undergraduate medical students on artificial intelligence in medicine: mixed-methods survey study from Palestine

Jebreen,

Radwan,

Kammoun-Rebai

et al. 2024

BMC Med Educ

View full text Add to dashboard Cite

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Artificial Intelligence: Knowledge and Attitude Among Lebanese Medical Students

Daher,

Dabbousi,

Chamroukh

et al. 2024

Cureus

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Background Artificial intelligence (AI) has taken on a variety of functions in the medical field, and research has proven that it can address complicated issues in various applications. It is unknown whether Lebanese medical students and residents have a detailed understanding of this concept, and little is known about their attitudes toward AI. Aim This study fills a critical gap by revealing the knowledge and attitude of Lebanese medical students toward AI. Methods A multi-centric survey targeting 365 medical students from seven medical schools across Lebanon was conducted to assess their knowledge of and attitudes toward AI in medicine. The survey consists of five sections: the first part includes socio-demographic variables, while the second comprises the 'Medical Artificial Intelligence Readiness Scale' for medical students. The third part focuses on attitudes toward AI in medicine, the fourth assesses understanding of deep learning, and the fifth targets considerations of radiology as a specialization. Results There is a notable awareness of AI among students who are eager to learn about it. Despite this interest, there exists a gap in knowledge regarding deep learning, albeit alongside a positive attitude towards it. Students who are more open to embracing AI technology tend to have a better understanding of AI concepts (p=0.001). Additionally, a higher percentage of students from Mount Lebanon (71.6%) showed an inclination towards using AI compared to Beirut (63.2%) (p=0.03). Noteworthy are the Lebanese University and Saint Joseph University, where the highest proportions of students are willing to integrate AI into the medical field (79.4% and 76.7%, respectively; p=0.001). Conclusion It was concluded that most Lebanese medical students might not necessarily comprehend the core technological ideas of AI and deep learning. This lack of understanding was evident from the substantial amount of misinformation among the students. Consequently, there appears to be a significant demand for the inclusion of AI technologies in Lebanese medical school courses.

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Artificial Intelligence Revolutionizing the Field of Medical Education

Cited by 2 publications

References 47 publications

Perceptions of undergraduate medical students on artificial intelligence in medicine: mixed-methods survey study from Palestine

Perceptions of undergraduate medical students on artificial intelligence in medicine: mixed-methods survey study from Palestine

Artificial Intelligence: Knowledge and Attitude Among Lebanese Medical Students

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