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Negation Detection in Clinical Reports Written in German
- Viviana Cotik, Roland Roller, Feiyu Xu, H. Uszkoreit, K. Budde, D. Schmidt
- Computer ScienceBioTxtM@COLING
- 1 December 2016
This work presents a system for detecting mentions of clinical findings that are negated or just speculated in German clinical texts, built on top of NegEx, a well known algorithm for identifying non-factive mentions of medical findings.
Findings of the WMT 2017 Biomedical Translation Shared Task
The second edition of the Biomedical Translation task in the Conference of Machine Translation focused on the automatic translation of biomedical-related documents between English and various European languages.
Towards the Automatic Classification of Offensive Language and Related Phenomena in German Tweets
In recent years the automatic detection of abusive language, offensive language and hate speech in several different forms of online communication has received a lot of attention by the Computational…
Self-supervised Relation Extraction Using UMLS
The presented results indicate that UMLS is a useful resource for semi-supervised relation extraction, a large biomedical knowledge base containing millions of concepts and relations among them, and is evaluated using two different techniques.
Cross-lingual Candidate Search for Biomedical Concept Normalization
This work proposes a cross-lingual candidate search for concept normalization using a character-based neural translation model trained on a multilingual biomedical terminology, showing that it outperforms most teams of CLEF eHealth 2015 and 2016 and can be run locally.
Applying UMLS for Distantly Supervised Relation Detection
This paper describes first results using the Unified Medical Language System (UMLS) for distantly supervised relation extraction using existing relation extraction data sets that contain relations that are similar to some of those in UMLS.
Improving distant supervision using inference learning
This work proposes a novel method for detecting potential false negative training examples using a knowledge inference method and shows that this approach improves the performance of relation extraction systems trained using distantly supervised data.
Overview of CLEF eHealth Task 1 - SpRadIE: A challenge on information extraction from Spanish Radiology Reports
The challenge aims at providing a standard evaluation framework to contribute to the advancement in the field of clinical natural language processing in Spanish, and is the first public challenge for named entity recognition and hedge cue detection for radiology reports in Spanish.
Identification of Genia Events using Multiple Classifiers
The system to extract genia events that was developed for the BioNLP 2013 Shared Task uses a supervised information extraction platform based on Support Vector Machines (SVM) and separates the process of event classification into multiple stages.
Natural vs. Synthesized Speech in Spoken Dialog Systems Research ?? Comparing the Performance of Recognition Results
- Tatjana Scheffler, Roland Roller, Florian Kretzschmar, S. Möller, Norbert Reithinger
- Computer ScienceITG Conference on Speech Communication
- 25 September 2012
A user simulation is used to connect speech synthesis to a real, state-of-the-art automatic speech recognition (ASR) component deployed in a working commercial SDS via a standard telephone line and shows that a good text-to-speech synthesis configuration rivals human speech both in recognition scores as well as variability.