Data-Driven Modeling of Randomized Controlled Trial Outcomes

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Zhehuan Chen, Yilu Fang, Hao Liu, Chunhua Weng

Published: 2022, Last Modified: 11 Feb 2026MIE 2022EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Anecdotally, 38.5% of clinical outcome descriptions in randomized controlled trial publications contain complex text. Existing terminologies are insufficient to standardize outcomes and their measures, temporal attributes, quantitative metrics, and other attributes. In this study, we analyzed the semantic patterns in the outcome text in a sample of COVID-19 trials and presented a data-driven method for modeling outcomes. We conclude that a data-driven knowledge representation can benefit natural language processing of outcome text from published clinical studies.