Generating summaries of hospitalizations: A new metric to assess the complexity of medical terms and their definitions

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Abstract

Our system generates summaries of hospital stays by combining information from two heterogenous sources: physician discharge notes and nursing plans of care. It extracts medical concepts from both sources; concepts that are identified as "complex" by our metric are explained by providing definitions obtained from three external knowledge sources. Finally, relevant concepts (with or without definition) are realized by SimpleNLG.

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Acharya, S., Eugenio, B. D., Boyd, A. D., Lopez, K. D., Cameron, R., & Keenan, G. M. (2016). Generating summaries of hospitalizations: A new metric to assess the complexity of medical terms and their definitions. In INLG 2016 - 9th International Natural Language Generation Conference, Proceedings of the Conference (pp. 26–30). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w16-6604

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