Nahid: AI-based Algorithm for operating fully-automatic surgery
This addresses the challenge of automating medical surgery, potentially improving precision and efficiency in healthcare, though it appears incremental as it builds on existing computer vision techniques.
The paper tackles the problem of fully automated surgery by proposing an AI-based algorithm, specifically using a U-net trained to detect and treat isolated ovarian endometriosis during surgery as proof of concept.
In this paper, for the first time, a method is presented that can provide a fully automated surgery based on software and computer vision techniques. Then, the advantages and challenges of computerization of medical surgery are examined. Finally, the surgery related to isolated ovarian endometriosis disease has been examined, and based on the presented method, a more detailed algorithm is presented that is capable of automatically diagnosing and treating this disease during surgery as proof of our proposed method where a U-net is trained to detect the endometriosis during surgery.