Papers with PICO

5 papers
A Corpus with Multi-Level Annotations of Patients, Interventions and Outcomes to Support Language Processing for Medical Literature (P18-1)

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Challenge: In 2015 alone, about 100 manuscripts describing randomized controlled trials for medical interventions were published every day.
Approach: They propose a corpus of 5,000 medical articles annotated with demarcations of text spans that describe the Patient population enrolled, the Interventions studied and to what they were Compared, and the Outcomes measured.
Outcome: The proposed corpus includes 5,000 medical articles describing clinical randomized controlled trials.
Medical Entity Corpus with PICO elements and Sentiment Analysis (L18-1)

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Challenge: In this paper, we establish a PICO and a sentiment annotated corpus of clinical trial publications.
Approach: They propose to create a phrase-level PICO corpus and a sentence-level sentiment annotated corpus from clinical trial publications.
Outcome: The proposed corpus is annotated on a phrase-level and a sentiment annotation on the same corpus.
Improving Factuality in Clinical Abstractive Multi-Document Summarization by Guided Continued Pre-training (2024.naacl-short)

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Challenge: Existing methods for enhancing the factual accuracy of abstractive summarization models are not effective in fact-critical domains like clinical document summarizing.
Approach: They propose a guided continued pre-training stage for encoder-decoder models followed by supervised fine-tuning on summarization.
Outcome: The proposed approach improves the quality and factuality of the summaries and achieves the best-published results on the clinical document summarization task.
Sent2Span: Span Detection for PICO Extraction in the Biomedical Text without Span Annotations (2021.findings-emnlp)

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Challenge: Experiments show that PICO span detection results achieve much higher results for recall when compared to fully supervised methods.
Approach: They propose to extract and then normalise PICO information from clinical trial articles and use crowdsourced sentence-level annotations to detect spans.
Outcome: The proposed method achieves much higher results for recall when compared to fully supervised methods with PICO sentence detection at least as good as human annotations.
FactPICO: Factuality Evaluation for Plain Language Summarization of Medical Evidence (2024.acl-long)

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Challenge: FactPICO is a factuality benchmark for plain language summarization of medical texts describing randomized controlled trials . existing metrics for factual summarizing medical evidence are poorly correlated with expert judgments on the instance level.
Approach: They propose a factuality benchmark for plain language summarization of medical texts . they assess factuality of critical elements of RCTs in those summaries .
Outcome: The proposed benchmark assesses the factuality of medical summaries using LLMs . the summary summators are based on 345 plain language summaires with fine-grained evaluation .

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