Jordan Sanders


2020

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Extracting Adherence Information from Electronic Health Records
Jordan Sanders | Meghana Gudala | Kathleen Hamilton | Nishtha Prasad | Jordan Stovall | Eduardo Blanco | Jane E Hamilton | Kirk Roberts
Proceedings of the 28th International Conference on Computational Linguistics

Patient adherence is a critical factor in health outcomes. We present a framework to extract adherence information from electronic health records, including both sentence-level information indicating general adherence information (full, partial, none, etc.) and span-level information providing additional information such as adherence type (medication or nonmedication), reasons and outcomes. We annotate and make publicly available a new corpus of 3,000 de-identified sentences, and discuss the language physicians use to document adherence information. We also explore models based on state-of-the-art transformers to automate both tasks.

2016

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Automatic Extraction of Implicit Interpretations from Modal Constructions
Jordan Sanders | Eduardo Blanco
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing