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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 benefitdoi:10.3233/shti220481 pmid:35612103 fatcat:ji4ndvuhgva2leoffwmodayj3e