Negation recognition in medical narrative reports
Information Retrieval
Creating and evaluating a consensus for negated and speculative words in a Swedish clinical corpus
NeSp-NLP '10 Proceedings of the Workshop on Negation and Speculation in Natural Language Processing
Modality and negation: An introduction to the special issue
Computational Linguistics
Detection of evidence in clinical research papers
HIKM '12 Proceedings of the Fifth Australasian Workshop on Health Informatics and Knowledge Management - Volume 129
| Hi-index | 0.00 |
NegEx, a rule-based algorithm that detects negations in English clinical text, was translated into Swedish and evaluated on clinical text written in Swedish. The NegEx algorithm detects negations through the use of trigger phrases, which indicate that a preceding or following concept is negated. A list of English trigger phrases was translated into Swedish, taking grammatical differences between the two languages into account. This translation was evaluated on a set of 436 manually classified sentences from Swedish health records. The results showed a precision of 70% and a recall of 81% for sentences containing the trigger phrases and a negative predictive value of 96% for sentences not containing any trigger phrases. The precision was significantly lower for the Swedish adaptation than published results on the English version, but since many negated propositions were identified through a limited set of trigger phrases, it could nevertheless be concluded that the same trigger phrase approach is possible in a Swedish context, even though it needs to be further developed.