Yearbook of Medical Informatics, Table of Contents Yearb Med Inform 2010; 19(01): 64-67DOI: 10.1055/s-0038-1638691 Original Article Georg Thieme Verlag KG Stuttgart Knowledge Representation and Management Transforming Textual Information into Useful Knowledge A.-M. Rassinoux 1 Department of Imaging and Medical Informatics, Geneva University Hospitals, Geneva, Switzerland , Section Editor for the IMIA Yearbook Section on Knowledge Representation and Management › Author Affiliations Recommend Article Abstract Full Text PDF Download Keywords KeywordsStructured knowledge - natural language processing (NLP) - text mining - knowledge extraction - knowledge representation References References 1 Popowich F. Using text mining and natural language processing for health care claims processing. SIGKDD Exploration Newsletter 2005; 07 (01) 59-66. 2 Miyao Y, Sagae K, Saetre R, Matsuzaki T, Tsujii J. Evaluating contributions of natural language parsers to protein-protein interaction extraction. Bioinformatics 2009; Feb 1; 25 (03) 394-400. 3 Roos M, Marshall MS, Gibson AP, Schuemie M, Meij E, Katrenko S. et al. Structuring and extracting knowledge for the support of hypothesis generation in molecular biology. BMC Bioinformatics 2009; 10 Suppl 10 S9. 4 Meystre SM, Savova GK, Kipper-Schuler KC, Hurdle JF. Extracting information from textual documents in the electronic health record: a review of recent research. Yearb Med Inform 2008; 128-44. 5 Friedman C, Johnson S. Natural language and text processing in biomedicine. In: Shortliffe E, Cimino JJ. editors. Biomedical Informatics Computer Applications in Health Care and Biomedicine. 2006 6 Cohen AM, Hersh WR. A survey of current work in biomedical text mining. Brief Bioinform 2005; Mar; 06 (01) 57-71. 7 Rassinoux AM. Decision Support, Knowledge Representation and Management: Structuring Knowledge for Better Access. In: Geissbuhler A, Kulikowski C. editors. IMIA Yearbook of Medical Informatics 2008. Methods Inf Med 2008; 47 Suppl 1: 80-2. 8 Feigenbaum L, Herman I, Hongsermeier T, Neumann E, Stephens S. The Semantic Web in Action. Scientific American Magazine 2007; 297: 90-7. 9 https://cabig-kc.nci.nih.gov/Vocab/KC/index.php/OHNLP 10 Savova G, Kipper-Schuler KC, Buntrock J, Chute C. UIMA-based clinical information extraction system. Language Resources and Evaluation Conference 2008 (LREC) Towards enhanced interoperability for large HLT systems: UIMA for NLP; Marrakech. Morocco: 2008 11 Pakhomov J, Buntrock J, Duffy P. High throughput modularized NLP system for clinical text. In: Proceedings of the Association for Computational Linguistics (ACL’05) 2005; 25-8. 12 Coden A, Savova G, Sominsky I, Tanenblatt M, Masanz J, Schuler K. et al. Automatically extracting cancer disease characteristics from pathology reports into a Disease Knowledge Representation Model. J Biomed Inform 2009; Oct; 42 (05) 937-49. 13 Rassinoux AM. Decision Support, Knowledge Representation and Management: Towards Interoperable Medical terminologies. In: Geissbuhler A, Kulikowski C. editors. IMIAYearbook of Medical Informatics 2009. Methods Suppl. 2009: 99-102. 14 Rosenbloom ST, Brown SH, Froehling D, Bauer BA, Wahner-Roedler DL, Gregg WM. et al. Using SNOMED CT to Represent Two Interface Terminologies. J Am Med Inform Assoc 2009; Jan- Feb; 16 (01) 81-8. 15 Yu AC. Methods in biomedical ontology. J Biomed Inform 2006; 39: 252-66. 16 Rector AL, Brandt S. Why do it the hard way? The case for an expressive description logic for SNOMED. J Am Med Inform Assoc 2008; 15 (06) 744-51. 17 Chen ES, Maloney FL, Shilmayster E, Goldberg HS. Laying the groundwork for enterprise-wide medical language processing services: architecture and process. AMIA Annu Symp Proc 2009; Nov 14; 2009: 97-101.
