Automatic Mapping Between Brazilian Portuguese Clinical Terms and International Classification for Nursing Practice.

This study describes MappICNP, an automatic method for mapping between Brazilian Portuguese clinical narratives in free text and International Classification for Nursing Practice (ICNP) concepts. It's composed of six natural language processing rules, related to terms comparison. A set of 2,638 terms extracted from hospitals nursing notes was mapped. MappICNP helps to map 1,607 terms, 113 less than a manual approach. The results demostrate its advantages in minimizing the time spent and reducing the scope of analysis through candidate terms of ICNP.

Learning Portuguese Clinical Word Embeddings: A Multi-Specialty and Multi-Institutional Corpus of Clinical Narratives Supporting a Downstream Biomedical Task.

In this paper, we trained a set of Portuguese clinical word embedding models of different granularities from multi-specialty and multi-institutional clinical narrative datasets. Then, we assessed their impact on a downstream biomedical NLP task of Urinary Tract Infection disease identification. Additionally, we intrinsically evaluated our main model using an adapted version of Bio-SimLex for the Portuguese language. Our empirical results showed that the larger, coarse-grained model achieved a slightly better outcome when compared with the small, fine-grained model in the proposed task. Moreover, we obtained satisfactory results with Bio-SimLex intrinsic evaluation.