The generation of a corpus for clinical sentiment analysis

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Abstract

Clinical care providers express their judgments and observations towards the patient status in clinical narratives. In contrast to sentiment expressions in general domains targeted by language technology, clinical sentiments are influenced by related medical events such as clinical precondition or outcome of a treatment. We argue that patient status in terms of positive, negative and neutral judgements can only suboptimally be judged with generic approaches, and requires specific resources in term of a lexicon and training corpus targeting clinical sentiment. To address this challenge, we manually developed a corpus based on 300 ICU nurse letters derived from a clinical database, and an annotation scheme for clinical sentiment. The paper discusses influence patterns between clinical context and clinical sentiments as well as a semi-automatic method to generate a larger annotated corpus.

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CITATION STYLE

APA

Deng, Y., Declerck, T., Lendvai, P., & Denecke, K. (2016). The generation of a corpus for clinical sentiment analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9989 LNCS, pp. 311–324). Springer Verlag. https://doi.org/10.1007/978-3-319-47602-5_46

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