Toward a Human-Centered AI-assisted Colonoscopy System

TL;DR

This paper reviews recent AI-assisted colonoscopy systems, emphasizing the need for human-centered design by understanding clinicians' needs and usability challenges, especially in the Australian context.

Contribution

It introduces recent commercial systems, identifies gaps between clinician expectations and system capabilities, and highlights unique challenges faced in Australia.

Findings

Commercial systems mainly focus on visual detection of polyps.

Clinicians' needs and usability issues are underexplored.

Unique challenges in deploying AI-assisted colonoscopy in Australia.

Abstract

AI-assisted colonoscopy has received lots of attention in the last decade. Several randomised clinical trials in the previous two years showed exciting results of the improving detection rate of polyps. However, current commercial AI-assisted colonoscopy systems focus on providing visual assistance for detecting polyps during colonoscopy. There is a lack of understanding of the needs of gastroenterologists and the usability issues of these systems. This paper aims to introduce the recent development and deployment of commercial AI-assisted colonoscopy systems to the HCI community, identify gaps between the expectation of the clinicians and the capabilities of the commercial systems, and highlight some unique challenges in Australia.