Objectives: Focused cardiac ultrasound (FoCUS) is increasingly applied in many specialities, and adequate education and training of physicians is therefore mandatory. This study aimed to assess the impact of artificial intelligence (AI)-assisted interactive focused cardiac ultrasound (FoCUS) teaching session on undergraduate medical students’ confidence level and knowledge in cardiac ultrasound. Methods: The AI-assisted interactive FoCUS teaching session was held during the 9th National Undergraduate Cardiovascular Conference in London in March 2023 and all undergraduate medical students were invited to attend, and 79 students enrolled and attended the training. Two workshops were conducted each over 3-hour period. Each workshop consisted of a theoretical lecture followed by a supervised hands-on session by experts, first workshop trained 39 students and the second workshop trained 40 students. The students’ pre- and post-session knowledge and confidence levels were assessed by Likert-type-scale questionnaires filled in by the students before and immediately after the workshop. Results: A total of 61 pre-session and 52 post-session questionnaires were completed. Confidence level in ultrasound skills increased significantly for all six domains after the workshop, with the greatest improvement seen in obtaining basic cardiac views (p < 0.001 for all six domains). Students strongly agreed about the effectiveness of the teaching session and supported the integration of ultrasound training into their medical curriculum. Conclusions: AI-assisted interactive FoCUS training can be an effective and powerful tool to increase ultrasound skills and confidence levels of undergraduate medical students. Integration of such ultrasound courses into the medical curriculum should therefore be considered.
Soliman-Aboumarie, H., Geers, J., Lowcock, D., Suji, T., Kok, K., Cameli, M., et al. (2024). Artificial intelligence-assisted focused cardiac ultrasound training: A survey among undergraduate medical students. ULTRASOUND [10.1177/1742271X241287923].
Artificial intelligence-assisted focused cardiac ultrasound training: A survey among undergraduate medical students
Cameli M.;
2024-01-01
Abstract
Objectives: Focused cardiac ultrasound (FoCUS) is increasingly applied in many specialities, and adequate education and training of physicians is therefore mandatory. This study aimed to assess the impact of artificial intelligence (AI)-assisted interactive focused cardiac ultrasound (FoCUS) teaching session on undergraduate medical students’ confidence level and knowledge in cardiac ultrasound. Methods: The AI-assisted interactive FoCUS teaching session was held during the 9th National Undergraduate Cardiovascular Conference in London in March 2023 and all undergraduate medical students were invited to attend, and 79 students enrolled and attended the training. Two workshops were conducted each over 3-hour period. Each workshop consisted of a theoretical lecture followed by a supervised hands-on session by experts, first workshop trained 39 students and the second workshop trained 40 students. The students’ pre- and post-session knowledge and confidence levels were assessed by Likert-type-scale questionnaires filled in by the students before and immediately after the workshop. Results: A total of 61 pre-session and 52 post-session questionnaires were completed. Confidence level in ultrasound skills increased significantly for all six domains after the workshop, with the greatest improvement seen in obtaining basic cardiac views (p < 0.001 for all six domains). Students strongly agreed about the effectiveness of the teaching session and supported the integration of ultrasound training into their medical curriculum. Conclusions: AI-assisted interactive FoCUS training can be an effective and powerful tool to increase ultrasound skills and confidence levels of undergraduate medical students. Integration of such ultrasound courses into the medical curriculum should therefore be considered.File | Dimensione | Formato | |
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https://hdl.handle.net/11365/1278586