English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This paper describes the results of SemEval 2023 task 7 -- Multi-EvidenceNatural Language Inference for Clinical Trial Data (NLI4CT) -- consisting of 2tasks, a Natural Language Inference (NLI) task, and an evidence selection taskon clinical trial data. The proposed challenges require multi-hop biomedicaland numerical reasoning, which are of significant importance to the developmentof systems capable of large-scale interpretation and retrieval of medicalevidence, to provide personalized evidence-based care.  Task 1, the entailment task, received 643 submissions from 40 participants,and Task 2, the evidence selection task, received 364 submissions from 23participants. The tasks are challenging, with the majority of submitted systemsfailing to significantly outperform the majority class baseline on theentailment task, and we observe significantly better performance on theevidence selection task than on the entailment task. Increasing the number ofmodel parameters leads to a direct increase in performance, far moresignificant than the effect of biomedical pre-training. Future works couldexplore the limitations of large models for generalization and numericalinference, and investigate methods to augment clinical datasets to allow formore rigorous testing and to facilitate fine-tuning.  We envisage that the dataset, models, and results of this task will be usefulto the biomedical NLI and evidence retrieval communities. The dataset,competition leaderboard, and website are publicly available.

SemEval-2023 Task 7: Multi-Evidence Natural Language Inference for Clinical Trial Data