论文标题
与XPATH改善工作流程的整合:人类AI诊断系统的设计和评估
Improving Workflow Integration with xPath: Design and Evaluation of a Human-AI Diagnosis System in Pathology
论文作者
论文摘要
AI的最新发展提供了支持病理学家诊断的辅助工具。但是,将这些工具纳入病理学家的实践仍然是一项挑战。一个主要问题是AI与医疗决策的工作流程不足。我们观察到病理学家的检查,并发现整合AI的主要阻碍因素是它与病理学家的工作流程不兼容。为了弥合病理学家与AI之间的差距,我们开发了一种人类协作诊断工具-XPath,该工具与病理学家相似的检查过程可以改善AI在常规检查中的整合。 XPATH的生存能力通过技术评估和与十二个医学专业人员的工作评估证实。这项工作确定并解决了将AI模型纳入病理学的挑战,这可以提供有关HCI研究人员如何与医学专业人员并排合作的第一手知识,以将技术进步带入医疗任务,以实现实际应用。
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 twelve 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.