Towards sustainable clinical teaching in resource-limited settings: the potential role of an artificial intelligence (AI)-generated visual clinic

Background: Clinical teaching involves two essential parts, theory and clinical experience. The latter requires students to have an adequate level of contact with patients, but it can be affected by limited resources such as inadequate clinical facilities and months of industrial actions by healthcare workers in countries such as Nigeria. Although such a loss in learning opportunities can be lessened in other contexts with the use of clinical simulation tools, a lack of such resources is a challenge in resource-limited settings. Aim: The aim of this article is to present the use of an artificial intelligence (AI)-generated visual clinic, consisting of videos on the management of different diseases/conditions. Method: In this paper, topmedia AI (https://www.topmediai.com/app/text-to-video/) was used to generate videos of patients with stroke performing constraint-induced movement therapy (CIMT), motor imagery, sit-to-stand exercises, over-ground gait training and treadmill gait training using text prompts. After that, these different videos were combined together to form a stroke rehabilitation clinic. Result: A video of seemingly high quality showing patients undergoing stroke rehabilitation was produced. Conclusion: It is possible to generate videos of different diseases/conditions using AI, as it is very efficient, and catalogue them as a clinic for use in place of, or as an adjunct to, traditional clinical teaching. This may provide advantages for adequate clinical experience, access to rare and under-referred conditions/diseases, serving as succor during industrial actions, and as a means to reduce students’ exposure to dangers such as infections and harms. In addition, unlike traditional clinical hours, the AI-generated visual clinic will be opened for use to students for 24 hours.