Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

A single-institutional analysis of laparoscopic 3D radical cystectomy with intracorporeal urinary diversion.

BMC urology·2026

Same author

Ten-year update on the European Association of Urology Robotic Section (ERUS) fellowship training for robot-assisted radical prostatectomy.

BJUI compass·2026

Same author

Silent Messengers: The Role of Extracellular Vesicle-Associated miRNAs in the Non-Invasive Profiling of Hepatocellular Carcinoma.

Biomedicines·2026

Same author

Neoadjuvant Treatment Versus Upfront Surgery for Resectable Pancreatic Ductal Adenocarcinoma-A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Medicina (Kaunas, Lithuania)·2026

Same author

Real-Time Markerless Tooth Detection Towards Dynamic Robot-Assisted Dental Implant Navigation.

Dentistry journal·2026

Same author

Metabolomic Profiling of Plasma Bile Acids in Resectable Gastric Cancer.

Chirurgia (Bucharest, Romania : 1990)·2026

Search research articles

Related Experiment Video

Updated: Jul 23, 2025

Robotic Cochlear Implantation for Direct Cochlear Access

Robotic Cochlear Implantation for Direct Cochlear Access

Published on: June 16, 2022

Artificial Intelligence-Based Hazard Detection in Robotic-Assisted Single-Incision Oncologic Surgery.

Gabriela Rus¹, Iulia Andras², Calin Vaida¹

¹Research Center for Industrial Robots Simulation and Testing-CESTER, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania.

|July 14, 2023

Summary

This study introduces an AI and AR system for real-time detection of intraoperative bleeding during surgery. The system accurately identifies bleeding and displays alerts on a Hololens 2 device, enhancing surgical safety.

Keywords:

AI agents Hololens 2 YOLOv5 machine learning master–slave system parallel robotic system robotic-assisted single-incision surgery surgical oncology

More Related Videos

A Teleoperated Robotic System-Assisted Percutaneous Transiliac-Transsacral Screw Fixation Technique

A Teleoperated Robotic System-Assisted Percutaneous Transiliac-Transsacral Screw Fixation Technique

Published on: January 6, 2023

Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence

Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence

Published on: June 10, 2025

Related Experiment Videos

Last Updated: Jul 23, 2025

Robotic Cochlear Implantation for Direct Cochlear Access

Robotic Cochlear Implantation for Direct Cochlear Access

Published on: June 16, 2022

A Teleoperated Robotic System-Assisted Percutaneous Transiliac-Transsacral Screw Fixation Technique

A Teleoperated Robotic System-Assisted Percutaneous Transiliac-Transsacral Screw Fixation Technique

Published on: January 6, 2023

Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence

Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence

Published on: June 10, 2025

Area of Science:

Surgical Technology
Artificial Intelligence
Augmented Reality

Background:

Single-incision surgery presents unique challenges, with intraoperative hemorrhage being a significant complication, particularly in cancer patients.
Robotic assistance has improved surgical outcomes, but real-time hazard detection remains an area for advancement.

Purpose of the Study:

To develop and evaluate an Artificial Intelligence (AI) and Augmented Reality (AR) based hazard detection system for real-time identification of intraoperative bleeding.
To integrate this system with a Hololens 2 device for immediate visual feedback to surgeons.

Main Methods:

Exploration of real-time processing techniques, identifying YOLOv5 as a promising algorithm for bleeding detection.
Development of an innovative real-time bleeding detection system using YOLOv5 and Hololens 2.
Evaluation of the system across various surgical procedures and configurations to optimize prediction time and accuracy.

Main Results:

The system successfully detected intraoperative bleeding in multiple surgical procedures with high accuracy.
Detected bleeding areas were highlighted with bounding boxes and displayed on the Hololens 2.
The system effectively differentiated bleeding from irrigation, minimizing false-negative and false-positive results.

Conclusions:

Current AI and AR technologies are capable of developing effective real-time hazard detection systems.
Such systems can serve as valuable assistance tools for surgeons, particularly in high-risk surgical interventions.