Table of Contents.
Detailed Table of Contents.
1: Text Mining for Biomedicine.
2: Works at a Lexical Level: Crossroads Between NLP and Ontological Knowledge Management.
3: Lexical Granularity for Automatic Indexing and Means to Achieve It: The Case of Swedish Mesh®.
4: Expanding Terms with Medical Ontologies to Improve a Multi-Label Text Categorization System.
5: Using Biomedical Terminological Resources for Information Retrieval.
6: Automatic Alignment of Medical Terminologies with General Dictionaries for an Efficient Information Retrieval.
7: Translation of Biomedical Terms by Inferring Rewriting Rules.
8: Lexical Enrichment of Biomedical Ontologies.
9: Word Sense Disambiguation in Biomedical Applications: A Machine Learning Approach.
10: Going Beyond Words: NLP Approaches Involving the Sentence Level.
11: Information Extraction of Protein Phosphorylation from Biomedical Literature.
12: CorTag: A Language for a Contextual Tagging of the Words Within Their Sentence.
13: Analyzing the Text of Clinical Literature for Question Answering.
14: Pragmatics, Discourse Structures and Segment Level as the Last Stage in the NLP Offer to Biomedicine.
15: Discourse Processing for Text Mining.
16: A Neural Network Approach Implementing Non-Linear Relevance Feedback to Improve the Performance of Medical Information Retrieval Systems.
17: Extracting Patient Case Profiles with Domain-Specific Semantic Categories.
18: NLP Software for IR in Biomedicine.
19: Identification of Sequence Variants of Genes From Biomedical Literature: The OSIRIS Approach.
20: Verification of Uncurated Protein Annotations.
21: A Software Tool for Biomedical Information Extraction (And Beyond).
22: Problems-Solving Map Extraction with Collective Intelligence Analysis and Language Engineering.
23: Seekbio: Retrieval of Spatial Relations for System Biology.
24: Conclusion and Perspectives.
25: Analysing Clinical Notes for Translation Research: Back to the Future.
Compilation of References.
About the Contributors.