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Related Experiment Video

Updated: Apr 17, 2026

Translational Brain Mapping at the University of Rochester Medical Center: Preserving the Mind Through Personalized Brain Mapping

Translational Brain Mapping at the University of Rochester Medical Center: Preserving the Mind Through Personalized Brain Mapping

Published on: August 12, 2019

Specialized foundation models for intelligent operating rooms.

Ege Özsoy^1,2, Chantal Pellegrini^3,4, David Bani-Harouni^3,4

¹Munich Center for Machine Learning (MCML), Munich, Germany. ege.oezsoy@tum.de.

NPJ Digital Medicine

|April 15, 2026

Summary

This summary is machine-generated.

A new AI model, ORQA (Operating Room Question Answering), enhances surgical safety by understanding complex operating room data. It outperforms general AI, paving the way for smarter surgical technologies.

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Area of Science:

Artificial Intelligence in Medicine
Surgical Technology
Computer Vision

Background:

Surgical procedures require complex coordination of teams, tools, and imaging.
Current AI, like ChatGPT, excels in language but is insufficient for safety-critical, multimodal surgical environments.
Future operating rooms need intelligent systems for enhanced safety and efficiency.

Purpose of the Study:

To introduce ORQA, a multimodal foundation model for holistic surgical understanding.
To develop an AI capable of processing visual, auditory, and structured data in surgical settings.
To establish a foundation for next-generation intelligent surgical solutions.

Main Methods:

Developed ORQA, a multimodal foundation model integrating visual, auditory, and structured data.
Designed a question-answering framework for diverse surgical tasks.
Benchmarked ORQA against generalist vision-language models.
Released a family of smaller ORQA models for varied computational needs.

Main Results:

ORQA demonstrates substantially stronger and more consistent performance in perceiving surgical scenes compared to generalist models.
The model effectively unifies diverse data types for comprehensive surgical understanding.
A range of ORQA models were created to suit different deployment requirements.

Conclusions:

ORQA provides a foundational AI for intelligent surgical solutions.
The model enables surgical teams and technology providers to create safer and smarter operating rooms.
This work advances AI's role in critical healthcare applications like surgery.