Applications of Artificial Intelligence in Minimally Invasive Surgery Training: A Scoping Review - Daniel Caballero; Juan A. Sánchez-Margallo; Manuel J. Pérez-Salazar; Francisco M. Sánchez-Margallo (Surgeries)
Background/Objectives: Among the scientific literature, the significant potential of the application of artificial intelligence (AI) in minimally invasive surgery (MIS) stands out. The aim of this study is to provide a comprehensive review to analyze the scientific literature on AI applications in MIS training, selecting the main applications, limitations, opportunities and challenges in this field of research. Methods/Design: A literature search was conducted in scientific databases. The search was performed with titles or abstracts, using keywords. First, studies unrelated to the topic of study were eliminated. Next, the selection was limited to articles in English. The exclusion criteria for the search were reviews, letters, case reports, industrial articles and conference abstracts. Next, only studies published in the last ten years (2014–2024) were evaluated, with priority given to publications in the last five years (2019–2024) in surgical training in AI and MIS. Finally, the full text was reviewed to add or exclude the study from this review. Results: Of the 54 studies included in this review, 18 studies were related to skills assessment, 30 studies analyzed aspects of surgical training itself, 12 studies were related to learning aspects of surgical planning, 7 studies were based on gesture recognition and 3 studies were based on surgical action recognition to measure surgical performance during MIS training. A brief description of the main AI techniques was included in this review. Conclusions: The application of AI in MIS surgical training is still a developing field of research, which presents great potential for exploring future applications, challenges, opportunities and drawbacks, as well as synergies between the technical and clinical research fields.