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A corpus of potentially contradictory research claims from cardiovascular research abstracts
Abdulaziz Alamri1, Mark Stevenson2
1Department of Computer Science, The University of Sheffield, Sheffield, UK. adalamri1@sheffield.ac.uk.
Insights
This study developed a new corpus of contradictory biomedical claims from cardiovascular disease literature. This resource aids in creating automated methods to identify conflicting research findings.
Area of Science:
- Biomedical Informatics
- Medical Research Analysis
Background:
- Biomedical literature contains numerous treatment effectiveness claims, often inconsistent or contradictory.
- Identifying these contradictions is crucial for reliable information retrieval.
- A lack of suitable resources has hindered automated contradiction detection research.
Purpose of the Study:
- To develop a methodology for creating a corpus of contradictory research claims.
- To provide a resource for advancing automated contradiction identification in biomedicine.
- To demonstrate the application of this corpus in identifying claims from cardiovascular disease literature.
Main Methods:
- Systematic reviews on cardiovascular disease topics were identified from Medline.
- Annotators analyzed abstracts from these reviews to identify claims relevant to the review's question.
- Claims were categorized by their relation to the question and type.
Main Results:
- A corpus of 259 abstracts from 24 systematic reviews was created.
- High inter-annotator agreement was achieved, indicating reliable data.
- The corpus focuses on potentially contradictory claims within cardiovascular disease research.
Conclusions:
- A methodology for constructing a biomedical contradictory claims corpus was established.
- The developed corpus is publicly available to support further research.
- This resource facilitates the development of automated contradiction identification tools.
Background:
Research literature in biomedicine and related fields contains a huge number of claims, such as the effectiveness of treatments. These claims are not always consistent and may even contradict each other. Being able to identify contradictory claims is important for those who rely on the biomedical literature. Automated methods to identify and resolve them are required to cope with the amount of information available. However, research in this area has been hampered by a lack of suitable resources. We describe a methodology to develop a corpus which addresses this gap by providing examples of potentially contradictory claims and demonstrate how it can be applied to identify these claims from Medline abstracts related to the topic of cardiovascular disease.
Methods:
A set of systematic reviews concerned with four topics in cardiovascular disease were identified from Medline and analysed to determine whether the abstracts they reviewed contained contradictory research claims. For each review, annotators were asked to analyse these abstracts to identify claims within them that answered the question addressed in the review. The annotators were also asked to indicate how the claim related to that question and the type of the claim.
Results:
A total of 259 abstracts associated with 24 systematic reviews were used to form the corpus. Agreement between the annotators was high, suggesting that the information they provided is reliable.
Conclusions:
The paper describes a methodology for constructing a corpus containing contradictory research claims from the biomedical literature. The corpus is made available to enable further research into this area and support the development of automated approaches to contradiction identification.
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