English(EN) RECITE: Revising Eligibility Criteria Incorporating Textual Evidence

新的RECITE框架使用LLM修订临床试验资格标准

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-02 05:00

研究人员开发了RECITE框架，旨在自动化发现、提取和实施基于证据的临床试验资格标准修订过程。该系统利用方案修正文件创建了一个包含11,913个实例的数据集，将原始标准与支持性证据和拟议的更改进行配对。通过对各种LLM配置进行基准测试，研究发现Gemma 2 9B和GPT-4o表现相当，在经过领域专家验证的LLM-as-judge协议中取得了高分。该框架还通过一个代理式文献发现系统识别了44个相关的论文-试验匹配项，表明现有的临床知识可以被操作化以改进试验设计。 AI

影响该框架可以通过利用LLM分析和更新资格标准来简化临床试验设计，从而可能加速研究和患者招募。

排序理由该条目是一篇学术论文，详细介绍了一个新框架及其评估。[lever_c_demoted from research: ic=1 ai=1.0]

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Signal score: 0 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 该条目是一篇学术论文，详细介绍了一个新框架及其评估。[lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics: paper, product; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
Story freshness: 8 days old; Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

完整方法见我们的编辑标准。

报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Russell Ro, Reza Abbasi-Asl · 2026-11-02 05:00

RECITE: Revising Eligibility Criteria Incorporating Textual Evidence

arXiv:2610.41368v1 Announce Type: new Abstract: Overly restrictive eligibility criteria contribute to widespread enrollment failure in clinical trials, yet published recommendations for how specific criteria should be broadened remain disconnected from trial design at scale. We i…

本文如何被排名

报道来源 [1]

RECITE: Revising Eligibility Criteria Incorporating Textual Evidence

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