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New benchmark suite AMEND++ predicts clinical trial eligibility criteria amendments

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced AMEND++, a new benchmark suite designed to predict amendments to clinical trial eligibility criteria. This suite includes two datasets: AMEND, which tracks historical edits and amendment labels from public trials, and AMEND_LLM, a curated subset focused on substantive changes. They also developed Change-Aware Masked Language Modeling (CAMLM), a pretraining strategy that uses historical edits to improve amendment prediction, showing consistent gains across various baseline models. AI

IMPACT Could streamline clinical trial processes by predicting costly amendments.

RANK_REASON The cluster contains an academic paper introducing a new benchmark suite and methodology for a specific NLP task. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New benchmark suite AMEND++ predicts clinical trial eligibility criteria amendments

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The cluster contains an academic paper introducing a new benchmark suite and methodology for a specific NLP task. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Trisha Das, Mandis Beigi, Jacob Aptekar, Jimeng Sun ·

    $\texttt{AMEND++}$: Benchmarking Eligibility Criteria Amendments in Clinical Trials

    arXiv:2601.06300v2 Announce Type: replace Abstract: Clinical trial amendments frequently introduce delays, increased costs, and administrative burden, with eligibility criteria being the most commonly amended component. We introduce \textit{eligibility criteria amendment predicti…

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