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Abstract: There is a growing need for automated methods to better synthesize patient data from electronic health records (EHRs) and reduce the cognitive burden in clinical decision-making process for providers. In this study, we describe our effort to create a semantic textual similarity (STS) resource consisting of sentence pairs from clinical notes with semantic similarity assigned by clinical experts.

Learning Objective 1: Semantic Textual Similarity

Authors:

Naveed Afzal (Presenter)
Mayo Clinic

Yanshan Wang, Mayo Clinic
Feichen Shen, Mayo Clinic
Liwei Wang, Mayo Clinic
Hongfang Liu, Mayo Clinic

Presentation Materials:

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