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Open challenges for the automatic synthesis of clinical trials
Olivia Sanchez-Graillet1, David M Schmidt2, Christian Kullik3
1Semantic Computing Group, Center for Cognitive Interaction Technology, Bielefeld University, Inspiration 1, 33619, Bielefeld, NRW, Germany. olivia.sanchez@uni-bielefeld.de.
Objective:
An important criterion for selecting clinical trials to be compared in systematic reviews and meta-analyses is that they measure the same outcomes. However, this represents a challenge as there is a wide variety of outcomes, and it is difficult to standardize them for comparing clinical trials containing them. To address this challenge, we utilized our annotated dataset, which includes 211 abstracts of clinical trials related to glaucoma and type 2 diabetes mellitus. We then developed a tool that provides an overview of the annotated clinical trial information and enables users to group them by outcomes.
Results:
Using our visualization tool, we formed groups of outcomes and their respective clinical trials. We were able to determine the most common outcomes in clinical trials for these diseases. As a case study on diabetes, we compared our outcomes with those consented by diabetes stakeholders and found that many of the grouped outcomes are aligned with the consented ones. This demonstrates that tools such as the one presented can help standardize clinical outcomes, which in turn help in the synthesis of clinical trials. Finally, we also offer some recommendations that could help in the automation of clinical trials based on outcome standardization.
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