DC3 --用于临床决策支持的诊断案例挑战集
DC3 -- A Diagnostic Case Challenge Collection for Clinical Decision Support
摘要：
在临床护理中，获得正确的诊断是成功治疗和最终康复的第一步。根据案件的复杂性，诊断阶段可能很长，并充满错误和延误。这种错误很可能会导致患者严重伤害甚至导致他们死亡，据估计，美国医疗保健系统每年要花费数千亿美元。为了避免诊断错误，医生越来越多地依赖于诊断决策支持系统，这些系统来自医学、历史病例、教科书、临床指南和学术生物医学文献。然而，对这类系统的评价往往是以临时的方式进行的，使用的是不透明的方法和专有数据。本文介绍了DC 3，收集了31个极其困难的诊断病例挑战，由临床专家手动编译和解决。对于每种情况下，我们提出了一些时间顺序的医生产生的意见，以及最终确认的真正诊断。我们还提供了推断密集的相关性判断，这些情况下，在PubMed收集的2700万学术生物医学文章。
英文摘要：
In clinical care, obtaining a correct diagnosis is the first step towards successful treatment and, ultimately, recovery. Depending on the complexity of the case, the diagnostic phase can be lengthy and ridden with errors and delays. Such errors have a high likelihood to cause patients severe harm or even lead to their death and are estimated to cost the U.S. healthcare system several hundred billion dollars each year. To avoid diagnostic errors, physicians increasingly rely on diagnostic decision support systems drawing from heuristics, historic cases, textbooks, clinical guidelines and scholarly biomedical literature. The evaluation of such systems, however, is often conducted in an ad-hoc fashion, using non-transparent methodology, and proprietary data. This paper presents DC3, a collection of 31 extremely difficult diagnostic case challenges, manually compiled and solved by clinical experts. For each case, we present a number of temporally ordered physician-generated observations alongside the eventually confirmed true diagnosis. We additionally provide inferred dense relevance judgments for these cases among the PubMed collection of 27 million scholarly biomedical articles.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
