Improving Workflow Integration with xPath: Design and Evaluation of a Human-AI Diagnosis System in Pathology
Improving Workflow Integration with xPath: Design and Evaluation of a Human-AI Diagnosis System in Pathology
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DOI：
10.1145/3577011
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发表时间：
2023-04-01
影响因子：
3.7
通讯作者：
Chen, Xiang Anthony
中科院分区：
文献类型：
--
作者：
Gu, Hongyan;Liang, Yuan;Chen, Xiang Anthony
人工智能的最新发展为支持病理学家的诊断提供了辅助工具。然而，将这些工具纳入病理学家的实践中仍然具有挑战性；一个主要问题是人工智能与医疗决策的工作流程集成不足。我们观察了病理学家的检查，发现人工智能集成的主要阻碍因素是它与病理学家工作流程的不兼容。为了弥合病理学家和人工智能之间的差距，我们开发了一种人机协作诊断工具xPath，它与病理学家具有类似的检查流程，可以提高人工智能与病理学家日常检查的融合。 xPath 的可行性得到了技术评估和 12 名病理学医疗专业人员的工作会议的证实。这项工作确定并解决了将人工智能模型纳入病理学的挑战，这可以提供关于人机交互研究人员如何与医疗专业人员并肩合作，将技术进步带入医疗任务的实际应用的第一手知识。
Recent developments in AI have provided assisting tools to support pathologists' diagnoses. However, it remains challenging to incorporate such tools into pathologists' practice; one main concern is AI's insufficient workflow integration with medical decisions. We observed pathologists' examination and discovered that the main hindering factor to integrate AI is its incompatibility with pathologists' workflow. To bridge the gap between pathologists and AI, we developed a human-AI collaborative diagnosis tool- xPath -that shares a similar examination process to that of pathologists, which can improve AI's integration into their routine examination. The viability of xPath is confirmed by a technical evaluation and work sessions with 12 medical professionals in pathology. This work identifies and addresses the challenge of incorporating AI models into pathology, which can offer first-hand knowledge about how HCI researchers can work with medical professionals side-by-side to bring technological advances to medical tasks towards practical applications.