arXiv · cs.AI · Russell Ro, Reza Abbasi-Asl · 10 小时前模型评分44
RECITE：用文本证据自动修订临床试验入组标准
RECITE: Revising Eligibility Criteria Incorporating Textual Evidence
导读
研究团队提出 RECITE 框架，可从方案修订文档中自动发现、抽取并落实有证据支持的入组标准修订，并基于 5,735 项试验构建了 11,913 条配对数据集。
分类置信度
中 · 待人工复核
- 存在未解决的相邻类别：ai-tooling、foundation-models，需要人工复核。
- 只有单一媒体来源，需要人工复核。
来源级别：媒体与个人
应用领域：医疗与生命科学
事件类型：研究发布
证据摘录
- “We introduce RECITE (Revising Eligibility Criteria Incorporating Textual Evidence), a framework for automated discovery, extraction, and implementation of evidence-based eligibility criteria revisions.”
- “RECITE uses protocol amendment documents from this http URL to construct a dataset of 11,913 curated instances across 5,735 trials, each pairing original criteria with documentary evidence and target revisions.”
- “We benchmark fifteen LLM configurations under truncated-to-context-window and retrieval-augmented generation conditions, on a 3,116-instance sample under an LLM-as-judge protocol validated against ten domain experts (judge vs. human quadratic-weighted Cohen's $\kappa_{qw} = 0.694 \pm 0.096$).”
来源：arXiv · cs.AI · arxiv.org