# Roadmap to Autonomous Surgery -- A Framework to Surgical Autonomy

arXiv: https://arxiv.org/abs/2206.10516 · HTML: https://mlsanity.com/paper/2206.10516/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 38 references that are in the map.
- First posted on arXiv 26 May 2022.

## Builds on (most cited first, 4 of 4)

- [Manipulating Soft Tissues by Deep Reinforcement Learning for Autonomous Robotic Surgery](https://mlsanity.com/paper/1902.05183/) (2019)
- [Robotic Surgery With Lean Reinforcement Learning](https://mlsanity.com/paper/2105.01006/) (2021)
- [Robotic Endoscope Control via Autonomous Instrument Tracking](https://mlsanity.com/paper/2107.02317/) (2021)
- [Medical Technologies and Challenges of Robot Assisted Minimally Invasive Intervention and Diagnostics](https://mlsanity.com/paper/1807.03731/) (2018)

## Built on by (most cited first, 1 of 1)

- [Autonomous Soft Tissue Retraction Using Demonstration-Guided Reinforcement Learning](https://mlsanity.com/paper/2309.00837/) (2023)

## Abstract (arXiv)

Robotic surgery has increased the domain of surgeries possible. Several examples of partial surgical automation have been seen in the past decade. We break down the path of automation tasks into features required and provide a checklist that can help reach higher levels of surgical automation. Finally, we discuss the current challenges and advances required to make this happen.