Artificial Intelligence in Surgery: Neural Networks and Deep Learning

TL;DR

This paper discusses the potential and challenges of applying deep neural networks and deep learning in surgical practices, emphasizing collaboration between surgeons and computer scientists for effective implementation.

Contribution

It provides an overview of deep learning concepts tailored for surgeons and highlights the specific challenges of deploying neural networks in surgical settings.

Findings

Deep learning can enhance surgical decision-making and diagnostics.

Collaboration between surgeons and AI researchers is crucial for successful implementation.

Understanding neural networks helps surgeons adopt AI tools effectively.

Abstract

Deep neural networks power most recent successes of artificial intelligence, spanning from self-driving cars to computer aided diagnosis in radiology and pathology. The high-stake data intensive process of surgery could highly benefit from such computational methods. However, surgeons and computer scientists should partner to develop and assess deep learning applications of value to patients and healthcare systems. This chapter and the accompanying hands-on material were designed for surgeons willing to understand the intuitions behind neural networks, become familiar with deep learning concepts and tasks, grasp what implementing a deep learning model in surgery means, and finally appreciate the specific challenges and limitations of deep neural networks in surgery. For the associated hands-on material, please see https://github.com/CAMMA-public/ai4surgery.