# Traffic Light Coding System for Engaging With AI in Surgery

**Authors:** Payal Mukherjee, Amin Beheshti, Shivani Angelique Kumar, Gordon Wallace, Neil Merrett, Jonathan Clark, Simon Kos, Ellen Rawstron, Jian Yang, Stuart Grieve, Amith Shetty, Simon Singer

PMC · DOI: 10.1111/ans.70172 · Anz Journal of Surgery · 2025-05-15

## TL;DR

This paper introduces a traffic light coding system to help surgeons understand and engage with AI technologies in healthcare.

## Contribution

The novel contribution is a structured framework for surgeons to evaluate and apply AI systems in medical practice.

## Key findings

- AI systems are increasingly used in healthcare due to global crises like the pandemic.
- Surgeons need to understand different AI types and their applications for effective use.
- A traffic light coding system is proposed to guide engagement with AI technologies.

## Abstract

Artificial Intelligence (AI) is generally defined as the development of computer systems or machines that can perform tasks typically requiring human intelligence and is increasingly being used in modern healthcare. While, various AI systems have existed for decades, its scale in healthcare has been escalated by global crises such as the COVID‐19 pandemic and military conflicts, which has demanded rapid implementation of health system processes that improve efficiency in resource constrained environments. As AI‐enabled technologies gain prominence, it is vital for surgeons to understand the various types of AI systems and their applications in medical practice.

## Full-text entities

- **Diseases:** COVID-19 (MESH:D000086382)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## References

24 references — full list in the complete paper: https://tomesphere.com/paper/PMC12571954/full.md

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Source: https://tomesphere.com/paper/PMC12571954