Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Learning the scope of negation in biomedical texts
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Medical-Image Retrieval Based on Knowledge-Assisted Text and Image Indexing
IEEE Transactions on Circuits and Systems for Video Technology
A semantic graph-based approach to biomedical summarisation
Artificial Intelligence in Medicine
Editorial: COMPENDIUM: A text summarization system for generating abstracts of research papers
Data & Knowledge Engineering
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Physicians often use information from previous clinical cases in their decision-making process. However, the large amount of patient records available in hospitals makes an exhaustive search unfeasible. We propose a method for the retrieval of similar clinical cases, based on mapping the text onto UMLS concepts and representing the patient records as semantic graphs. The method also deals with the problems of negation detection and concept identification in clinical free text. To evaluate the approach, an evaluation collection has been developed. The results show that our method correlates well with the expert judgments and outperforms remarkably the traditional term-vector space model.