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OBJECTIVE: A scoping review of the literature was conducted to identify intraoperative AI applications for robotic surgery under development and categorise them by 1) purpose of the applications, 2) level of autonomy, 3) stage of development, and 4) type of measured outcome. BACKGROUND: In robotic surgery, artificial intelligence (AI) based applications have the potential to disrupt a field so far based on a master-slave paradigm. However, there is no available overview about this technology's current stage of development and level of autonomy. METHODS: MEDLINE and EMBASE were searched between January 1st 2010 and May 21st 2022. Abstract screening, full text review and data extraction were performed independently by two reviewers. Level of autonomy was defined according to the Yang et al classification and stage of development according to the IDEAL framework. RESULTS: 129 studies were included in the review. 97 studies (75%) described applications providing Robot Assistance (autonomy level 1), 30 studies (23%) application enabling Task Autonomy (autonomy level 2), and two studies (2%) application achieving Conditional autonomy (autonomy level 3). All studies were at IDEAL stage 0 and no clinical investigations on humans were found. 116 (90%) conducted in silico or ex-vivo experiments on inorganic material, 9 (7%) ex-vivo experiments on organic material, and 4 (3%) performed in vivo experiments in porcine models. CONCLUSION: Clinical evaluation of intraoperative AI applications for robotic surgery is still in its infancy and most applications have a low level of autonomy. With increasing levels of autonomy, the evaluation focus seems to shift from AI-specific metrics to process outcomes, although common standards are needed to allow comparison between systems.

Original publication




Journal article


Ann surg

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