Article citationsMore>>

Isensee, F., Jaeger, P.F., Kohl, S.A.A., Petersen, J. and Maier-Hein, K.H. (2020) NNU-Net: A Self-Configuring Method for Deep Learning-Based Biomedical Image Segmentation. Nature Methods, 18, 203-211.
https://doi.org/10.1038/s41592-020-01008-z

has been cited by the following article:

• TITLE: A Prototype AI Surgical Assistant for Real-Time Consultation during Laparoscopic Surgery

  AUTHORS: Savvas Hirides, Petros Hirides, Kalliopi Kouloufakou, Constantinos Hirides

  KEYWORDS: AI Surgical Assistant, Real-Time Video Analysis, GPT-4o in Surgery, AI in the OR, Voice-Activated Intraoperative Support

  JOURNAL NAME: Surgical Science, Vol.16 No.7, July 31, 2025

  ABSTRACT: Recent advancements in generative AI and large language models (LLMs) have sparked new opportunities in surgical innovation. We present our prototype AI Surgical Assistant Prototype System, integrating real-time vision support for streaming video of the operative field, advanced speech recognition, multilingual natural voice interaction, both long- and short-term memory simulation, and customizable behavioral profiles. Testing showed that the system exhibited contextual awareness from visual feedback in 38% of instances, ability for verbal interaction, and dynamic memory logging throughout the procedure. This feasibility study suggests that real-time, context-aware AI support is technically viable in the OR and may serve as a basis for future clinical models.