Toward a Human-Centered AI-assisted Colonoscopy System in Australia

• URL: http://arxiv.org/abs/2503.20790v1
• Date: Sat, 15 Mar 2025 23:36:48 GMT
• Title: Toward a Human-Centered AI-assisted Colonoscopy System in Australia
• Authors: Hsiang-Ting Chen, Yuan Zhang, Gustavo Carneiro, Rajvinder Singh,
• Abstract summary: Current development prioritizes machine learning model performance, overlooking essential aspects of user interface design, workflow integration, and overall user experience.<n>To realize AI's full potential, the HCI community must champion user-centered design, ensuring these systems are usable, support endoscopist expertise, and enhance patient outcomes.
• Score: 12.548421709213379
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: While AI-assisted colonoscopy promises improved colorectal cancer screening, its success relies on effective integration into clinical practice, not just algorithmic accuracy. This paper, based on an Australian field study (observations and gastroenterologist interviews), highlights a critical disconnect: current development prioritizes machine learning model performance, overlooking essential aspects of user interface design, workflow integration, and overall user experience. Industry interactions reveal a similar emphasis on data and algorithms. To realize AI's full potential, the HCI community must champion user-centered design, ensuring these systems are usable, support endoscopist expertise, and enhance patient outcomes.

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