AI肠镜系统需以人为本，否则再准也难落地。
Toward a Human-Centered AI-assisted Colonoscopy System in Australia
- 从医生使用场景出发，强调界面与流程设计的重要性
- 澳洲实地调研发现算法性能≠临床可用性
- 适合关注AI医疗落地、人机协同的从业者
尽管人工智能辅助肠镜检查有望提升结直肠癌筛查效果，但其成功关键在于有效融入临床实践，而不仅依赖算法精度。本文基于澳大利亚的实地研究（观察记录与胃肠科医生访谈），揭示了一个核心矛盾：当前研发过度聚焦机器学习模型表现，忽视了用户界面设计、工作流程整合及整体用户体验。行业交流也反映出对数据与算法的单一侧重。要真正发挥AI潜力，人机交互（HCI）领域必须推动以用户为中心的设计，确保系统易用、支持内镜医师专业判断，并最终改善患者结局。
原文摘要 · Abstract (English)
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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