Artificial Intelligence (AI) brings advancements to support pathologists in navigating high-resolution tumor images to search for pathology patterns of interest. However, existing AI-assisted tools have not realized this promised potential due to a lack of insight into pathology and HCI considerations for pathologists' navigation workflows in practice. We first conducted a formative study with six medical professionals in pathology to capture their navigation strategies. By incorporating our observations along with the pathologists' domain knowledge, we designed NaviPath -- a human-AI collaborative navigation system. An evaluation study with 15 medical professionals in pathology indicated that: (i) compared to the manual navigation, participants saw more than twice the number of pathological patterns in unit time with NaviPath, and (ii) participants achieved higher precision and recall against the AI and the manual navigation on average. Further qualitative analysis revealed that navigation was more consistent with NaviPath, which can improve the overall examination quality.
翻译:人工智能(AI)带来进步,支持病理学家利用高分辨率肿瘤图象寻找感兴趣的病理学模式,然而,现有的人工智能辅助工具尚未实现这一潜力,原因是对病理学和HCI在实践中对病理学家导航工作流程的考虑缺乏洞察力;我们首先与病理学的6名医学专业人员进行了成型研究,以捕捉他们的导航战略;我们结合病理学家的域知识结合了我们的观测结果,设计了一个人类-人工智能协作导航系统;与15名病理学医学专业人员进行的评估研究表明:(一) 与人工导航相比,参与者看到的病理学模式在与纳维帕特的单时数是两倍以上;(二) 参与者比AI和人工导航平均达到更高的精确度和回顾度;进一步的质量分析显示,导航与Navipath更加一致,这可以提高总体检查质量。