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TASS 2018: The Strength of Deep Learning in Language Understanding Tasks
TLDR
Two new tasks focused on semantic relation extraction in the health domain and emotion classification in the news domain were added to the two traditional tasks of TASS, namely sentiment analysis at tweet level and aspect level.
Integrating MeSH Ontology to Improve Medical Information Retrieval
TLDR
The SINAI research group has participated in the multilingual image retrieval subtask and has used the MeSH ontology to expand the queries, and processed the set of collections using Information Gain in the same way as in ImageCLEFmed 2006.
Overview of TASS 2016
TLDR
The TASS 2016 proposed tasks, the description of the corpora used, the participant groups, the results and analysis of them are presented.
The University of Jaén at ImageCLEF 2005: Adhoc and Medical Tasks
TLDR
The SINAI research group participated in both the ad hoc task and the medical task, and used several translation schemes as well as experiments with and without Pseudo Relevance Feedback (PRF).
Transfer learning applied to text classification in Spanish radiological reports
TLDR
The use of transfer learning methods applied to the automatic detection of codes in radiological reports in Spanish using the BERT model applied to Spanish is presented.
Extracting Neoplasms Morphology Mentions in Spanish Clinical Cases through Word Embeddings
TLDR
This paper presents an automated system based on neural networks for the extraction of tumor morphology mentions in Spanish clinical cases using a Bidirectional variant of Long Short Term Memory (BiLSTM) neural network with a Conditional Random Fields (CRF) layer.
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