Tudor Groza


2016

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Building a dictionary of lexical variants for phenotype descriptors
Simon Kocbek | Tudor Groza
Proceedings of the 15th Workshop on Biomedical Natural Language Processing

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Evaluating a dictionary of human phenotype terms focusing on rare diseases
Simon Kocbek | Toyofumi Fujiwara | Jin-Dong Kim | Toshihisa Takagi | Tudor Groza
Proceedings of the 5th International Workshop on Computational Terminology (Computerm2016)

Annotating medical text such as clinical notes with human phenotype descriptors is an important task that can, for example, assist in building patient profiles. To automatically annotate text one usually needs a dictionary of predefined terms. However, do to the variety of human expressiveness, current state-of-the art phenotype concept recognizers and automatic annotators struggle with specific domain issues and challenges. In this paper we present results of an-notating gold standard corpus with a dictionary containing lexical variants for the Human Phenotype Ontology terms. The main purpose of the dictionary is to improve the recall of phenotype concept recognition systems. We compare the method with four other approaches and present results.

2015

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Similarity Metrics for Clustering PubMed Abstracts for Evidence Based Medicine
Hamed Hassanzadeh | Diego Moll√° | Tudor Groza | Anthony Nguyen | Jane Hunter
Proceedings of the Australasian Language Technology Association Workshop 2015

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UQeResearch: Semantic Textual Similarity Quantification
Hamed Hassanzadeh | Tudor Groza | Anthony Nguyen | Jane Hunter
Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)

2014

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Automated Generation of Test Suites for Error Analysis of Concept Recognition Systems
Tudor Groza | Karin Verspoor
Proceedings of the Australasian Language Technology Association Workshop 2014