AI-AUGMENTED ROBOTIC SURGERY IN UROGYNECOLOGY

Abstract

This paper will analyze the problem of using artificial intelligence (AI) in robotic-assisted surgery in urogynecology. This subject is concerned with ways on how it can make surgeries more accurate, be of less time, and better results of the said surgeries.  It was a mixed-methods experiment study in which a total of 120 patients were receiving minimally invasive procedures to treat pelvic organ prolapse and have urine incontinence.  They were randomly divided into two groups: one of them had routine robotic surgery and another one had AI-aided robotic surgery.  Those helped by AI achieved a substantial reduction in crucial indicators, including an abridged mean operative time (down 18 percent), reduced blood loss at the course of the surgery (down 21 percent), reduced complication rates (12 percent compared to 25 percent), and shorter postoperative hospital stays (an average span of 1.3 days).  The nerve-sparing and right placement of sutures were more accurate, too, with the help of A-enhanced visualizations in real-time.  In surgical teams, qualitative data indicated that AI brought about increased confidence, facilitated the working process, and assisted to be more oriented to the surrounding environment. But there were questions also as to how easy would it be to interpret AI and how quickly would it take to respond.  We could make accurate surgical outcome predictions, with an AUC of 0.91, by utilizing the deep learning algorithms in pre-operative predictive modeling. This indicates the confidence of AI in decision-making in an operation.  One possible solution is to employ AI in the field of robotic surgeries to enhance the shortcomings of the current state of minimal invasive surgeries, particularly in complex cases in pelvic surgeries.  This research is the foundation of ensuring that AI is implemented in the clinical surgical environment. It emphasizes the necessity of consistent enhancement of algorithms, training of surgeons, and development of moral constructs to help working with machines in the operation room.