Mp34-11 Distinguishing Surgical Expertise Using Machine Learning and Automated Performance Metrics During Sub-stitches of Vesico-urethral Anastomosis
Year: 2020
Type: article
Abstract: tomography images using the Synapse Vincent (Fuji Medical Systems, Tokyo, Japan) and HoloEyesXR (Holoeyes, Tokyo, Japan) software.Following completion of each training protocol, participants completed an anonymous questionnaire composed of 0-10 scale and openended questions assessing the utility of the training.RESULTS: 15 participants were enrolled in this study and they all completed the questionnaires.The median (range) age of the participants was 21 (21-23) years.The 3D organ model projection significantly improved assessment scores regarding the following 7 elements; anatomical acquisition, renal hilum inspection, self-efficacy to detect the kidney, self-efficacy to conduct renal US, ease of kidney detection, learning effect of the training, and recommendation to other students (p<0.05 for all).The most frequent answer to the open-ended question regarding why they thought MR technology was useful for US training was, "contribution to understanding the positional relationship between the abdominal organs."(13/15, 87%).CONCLUSIONS: Holographic 3D organ model projection from a wearable MR computer facilitates renal US training of medical students.
Source: The Journal of Urology
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W3022956103