{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T01:03:27Z","timestamp":1790039007714,"version":"4.0.1"},"reference-count":66,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2015,9,7]],"date-time":"2015-09-07T00:00:00Z","timestamp":1441584000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2015,9,7]],"date-time":"2015-09-07T00:00:00Z","timestamp":1441584000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Biomed Semant"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>In the realm of knee pathology, magnetic resonance imaging (MRI) has the advantage of visualising all structures within the knee joint, which makes it a valuable tool for increasing diagnostic accuracy and planning surgical treatments. Therefore, clinical narratives found in MRI reports convey valuable diagnostic information. A range of studies have proven the feasibility of natural language processing for information extraction from clinical narratives. However, no study focused specifically on MRI reports in relation to knee pathology, possibly due to the complexity of knee anatomy and a wide range of conditions that may be associated with different anatomical entities. In this paper we describe KneeTex, an information extraction system that operates in this domain.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>As an ontology\u2013driven information extraction system, KneeTex makes active use of an ontology to strongly guide and constrain text analysis. We used automatic term recognition to facilitate the development of a domain\u2013specific ontology with sufficient detail and coverage for text mining applications. In combination with the ontology, high regularity of the sublanguage used in knee MRI reports allowed us to model its processing by a set of sophisticated lexico\u2013semantic rules with minimal syntactic analysis. The main processing steps involve named entity recognition combined with coordination, enumeration, ambiguity and co\u2013reference resolution, followed by text segmentation. Ontology\u2013based semantic typing is then used to drive the template filling process.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We adopted an existing ontology, TRAK (Taxonomy for RehAbilitation of Knee conditions), for use within KneeTex. The original TRAK ontology expanded from 1,292 concepts, 1,720 synonyms and 518 relationship instances to 1,621 concepts, 2,550 synonyms and 560 relationship instances. This provided KneeTex with a very fine\u2013grained lexico\u2013semantic knowledge base, which is highly attuned to the given sublanguage. Information extraction results were evaluated on a test set of 100 MRI reports. A gold standard consisted of 1,259 filled template records with the following slots: finding, finding qualifier, negation, certainty, anatomy and anatomy qualifier. KneeTex extracted information with precision of 98.00\u00a0%, recall of 97.63\u00a0% and F\u2013measure of 97.81\u00a0%, the values of which are in line with human\u2013like performance.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>KneeTex is an open\u2013source, stand\u2013alone application for information extraction from narrative reports that describe an MRI scan of the knee. Given an MRI report as input, the system outputs the corresponding clinical findings in the form of JavaScript Object Notation objects. The extracted information is mapped onto TRAK, an ontology that formally models knowledge relevant for the rehabilitation of knee conditions. As a result, formally structured and coded information allows for complex searches to be conducted efficiently over the original MRI reports, thereby effectively supporting epidemiologic studies of knee conditions.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s13326-015-0033-1","type":"journal-article","created":{"date-parts":[[2015,9,7]],"date-time":"2015-09-07T06:10:48Z","timestamp":1441606248000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["KneeTex: an ontology\u2013driven system for information extraction from MRI reports"],"prefix":"10.1186","volume":"6","author":[{"given":"Irena","family":"Spasi\u0107","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bo","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher B.","family":"Jones","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kate","family":"Button","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2015,9,7]]},"reference":[{"key":"33_CR1","doi-asserted-by":"publisher","first-page":"1692","DOI":"10.1016\/j.joca.2014.06.005","volume":"22","author":"C Wenham","year":"2014","unstructured":"Wenham C, Grainger A, Conaghan P. The role of imaging modalities in the diagnosis, differential diagnosis and clinical assessment of peripheral joint osteoarthritis. Osteoarthr Cartil. 2014;22:1692\u2013702.","journal-title":"Osteoarthr Cartil"},{"key":"33_CR2","first-page":"221","volume":"85","author":"DC Pompan","year":"2012","unstructured":"Pompan DC. Reassessing the role of MRI in the evaluation of knee pain. Am Fam Physician. 2012;85:221\u20134.","journal-title":"Am Fam Physician"},{"key":"33_CR3","first-page":"247","volume":"85","author":"M Grover","year":"2012","unstructured":"Grover M. Evaluating acutely injured patients for internal derangement of the knee. Am Fam Physician. 2012;85:247\u201352.","journal-title":"Am Fam Physician"},{"key":"33_CR4","doi-asserted-by":"crossref","first-page":"w13314","DOI":"10.4414\/smw.2011.13314","volume":"141","author":"R Yan","year":"2011","unstructured":"Yan R, Wang H, Yang Z, Ji ZH, Guo YM. Predicted probability of meniscus tears: comparing history and physical examination with MRI. Swiss Med Wkly. 2011;141:w13314.","journal-title":"Swiss Med Wkly"},{"key":"33_CR5","doi-asserted-by":"publisher","first-page":"806","DOI":"10.1007\/s00167-009-0803-3","volume":"17","author":"S Konan","year":"2009","unstructured":"Konan S, Rayan F, Haddad FS. Do physical diagnostic tests accurately detect meniscal tears? Knee Surg Sports Traumatol Arthrosc. 2009;17:806\u201311.","journal-title":"Knee Surg Sports Traumatol Arthrosc"},{"key":"33_CR6","doi-asserted-by":"publisher","first-page":"1338","DOI":"10.1016\/j.injury.2008.06.021","volume":"39","author":"RAE Clayton","year":"2008","unstructured":"Clayton RAE, Court-Brown CM. The epidemiology of musculoskeletal tendinous and ligamentous injuries. Injury. 2008;39:1338\u201344.","journal-title":"Injury"},{"key":"33_CR7","doi-asserted-by":"publisher","first-page":"401","DOI":"10.1007\/s00167-011-1743-2","volume":"20","author":"FP Luyten","year":"2012","unstructured":"Luyten FP, Denti M, Filardo G, Kon E, Engebretsen L. Definition and classification of early osteoarthritis of the knee. Knee Surg Sports Traumatol Arthrosc. 2012;20:401\u20136.","journal-title":"Knee Surg Sports Traumatol Arthrosc"},{"key":"33_CR8","volume-title":"Standards for the reporting and interpretation of imaging investigations","author":"The Royal College of Radiologists","year":"2006","unstructured":"The Royal College of Radiologists. Standards for the reporting and interpretation of imaging investigations. 2006. http:\/\/www.rcr.ac.uk\/."},{"key":"33_CR9","first-page":"1804","volume":"70","author":"FW Roemer","year":"2011","unstructured":"Roemer FW, Guermazi A, Felson DT, Niu J, Nevitt MC, Crema MD, et al. Presence of MRI-detected joint effusion and synovitis increases the risk of cartilage loss in knees without osteoarthritis at 30-month follow-up: the MOST study. Clin Epidemiol Res. 2011;70:1804\u20139.","journal-title":"Clin Epidemiol Res"},{"key":"33_CR10","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.e5339","volume":"345","author":"A Guermazi","year":"2012","unstructured":"Guermazi A, Niu J, Hayashi D, Roemer F, Englund M, Neogi T, et al. Prevalence of abnormalities in knees detected by MRI in adults without knee osteoarthritis: population based observational study (Framingham Osteoarthritis Study). BMJ. 2012;345, e5339.","journal-title":"BMJ"},{"key":"33_CR11","doi-asserted-by":"publisher","first-page":"361","DOI":"10.1016\/S1063-4584(03)00049-9","volume":"11","author":"E Pessis","year":"2003","unstructured":"Pessis E, Drap\u00e9 J-L, Ravaud P, Chevrot A, Dougados M, Ayral X. Assessment of progression in knee osteoarthritis: Results of a 1\u00a0year study comparing arthroscopy and MRI. Osteoarthr Cartil. 2003;11:361\u20139.","journal-title":"Osteoarthr Cartil"},{"key":"33_CR12","doi-asserted-by":"publisher","first-page":"323","DOI":"10.1016\/j.joca.2009.11.002","volume":"18","author":"MK Javaid","year":"2010","unstructured":"Javaid MK, Lynch JA, Tolstykh I, Guermazi A, Roemer F, Aliabadi P, et al. Pre-radiographic MRI findings are associated with onset of knee symptoms: The MOST study. Osteoarthr Cartil. 2010;18:323\u20138.","journal-title":"Osteoarthr Cartil"},{"key":"33_CR13","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.0020124","volume":"2","author":"JPA Ioannidis","year":"2005","unstructured":"Ioannidis JPA. Why most published research findings are false. PLoS Med. 2005;2, e124.","journal-title":"PLoS Med"},{"key":"33_CR14","doi-asserted-by":"publisher","first-page":"365","DOI":"10.1038\/nrn3475","volume":"14","author":"KS Button","year":"2013","unstructured":"Button KS, Ioannidis JPA, Mokrysz C, Nosek BA, Flint J, Robinson ESJ, et al. Power failure: why small sample size undermines the reliability of neuroscience. Nat Rev Neurosci. 2013;14:365\u201376.","journal-title":"Nat Rev Neurosci"},{"key":"33_CR15","doi-asserted-by":"publisher","first-page":"605","DOI":"10.1016\/j.ijmedinf.2014.06.009","volume":"83","author":"I Spasi\u0107","year":"2014","unstructured":"Spasi\u0107 I, Livsey J, Keane J, Nenadi\u0107 G. Text mining of cancer-related information: review of current status and future directions. Int J Med Inform. 2014;83:605\u201323.","journal-title":"Int J Med Inform"},{"key":"33_CR16","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1186\/1471-2407-7-144","volume":"7","author":"SK Mohanty","year":"2007","unstructured":"Mohanty SK, Piccoli AL, Devine LJ, Patel AA, William GC, Winters SB, et al. Synoptic tool for reporting of hematological and lymphoid neoplasms based on World Health Organization classification and College of American Pathologists checklist. BMC Cancer. 2007;7:144.","journal-title":"BMC Cancer"},{"key":"33_CR17","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1136\/jamia.1994.95236146","volume":"1","author":"C Friedman","year":"1994","unstructured":"Friedman C, Alderson P, Austin J, Cimino J, Johnson S. A general natural-language text processor for clinical radiology. J Am Med Inform Assoc. 1994;1:161\u201374.","journal-title":"J Am Med Inform Assoc"},{"key":"33_CR18","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1148\/radiol.2241011118","volume":"224","author":"G Hripcsak","year":"2002","unstructured":"Hripcsak G, Austin JH, Alderson PO, Friedman C. Use of natural language processing to translate clinical information from a database of 889,921 chest radiographic reports. Radiology. 2002;224:157\u201363.","journal-title":"Radiology"},{"key":"33_CR19","first-page":"420","volume-title":"Proceedings of the AMIA Annual Symposium","author":"BW Mamlin","year":"2003","unstructured":"Mamlin BW, Heinze DT, McDonald CJ. Automated extraction and normalization of findings from cancer-related free-text radiology reports. In: Proceedings of the AMIA Annual Symposium. 2003. p. 420\u20134."},{"key":"33_CR20","doi-asserted-by":"publisher","first-page":"313","DOI":"10.2214\/AJR.07.3508","volume":"191","author":"PA Dang","year":"2008","unstructured":"Dang PA, Kalra MK, Blake MA, Schultz TJ, Halpern EF, Dreyer KJ. Extraction of recommendation features in radiology with natural language processing: exploratory study. Am J Roentgenol. 2008;191:313\u201320.","journal-title":"Am J Roentgenol"},{"key":"33_CR21","doi-asserted-by":"publisher","first-page":"663","DOI":"10.1148\/radiol.2513081346","volume":"251","author":"ES Burnside","year":"2009","unstructured":"Burnside ES, Davis J, Chhatwal J, Alagoz O, Lindstrom MJ, Geller BM, et al. Probabilistic computer model developed from clinical data in national mammography database format to classify mammographic findings. Radiology. 2009;251:663\u201372.","journal-title":"Radiology"},{"key":"33_CR22","doi-asserted-by":"publisher","first-page":"29","DOI":"10.3115\/1118149.1118154","volume-title":"ACL-02 Workshop on Natural Language Processing in the Biomedical Domain; Philadelphia, PA","author":"LM Christensen","year":"2002","unstructured":"Christensen LM, Haug PJ, Fiszman M. MPLUS: a probabilistic medical language understanding system. In: ACL-02 Workshop on Natural Language Processing in the Biomedical Domain; Philadelphia, PA. 2002. p. 29\u201336."},{"key":"33_CR23","doi-asserted-by":"publisher","first-page":"507","DOI":"10.1136\/jamia.2009.001560","volume":"17","author":"GK Savova","year":"2010","unstructured":"Savova GK, Masanz JJ, Ogren PV, Zheng J, Sohn S, Kipper-Schuler KC, et al. Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications. J Am Med Inform Assoc. 2010;17:507\u201313.","journal-title":"J Am Med Inform Assoc"},{"key":"33_CR24","doi-asserted-by":"publisher","first-page":"253","DOI":"10.1136\/jamia.2009.002295","volume":"17","author":"RS Crowley","year":"2010","unstructured":"Crowley RS, Castine M, Mitchell K, Chavan G, McSherry T, Feldman M. caTIES: a grid based system for coding and retrieval of surgical pathology reports and tissue specimens in support of translational research. J Am Med Inform Assoc. 2010;17:253\u201364.","journal-title":"J Am Med Inform Assoc"},{"key":"33_CR25","doi-asserted-by":"publisher","first-page":"937","DOI":"10.1016\/j.jbi.2008.12.005","volume":"42","author":"A Coden","year":"2009","unstructured":"Coden A, Savova G, Sominsky I, Tanenblatt M, Masanz J, Cooper KSJ, et al. Automatically extracting cancer disease characteristics from pathology reports into a Disease Knowledge Representation Model. J Biomed Inform. 2009;42:937\u201349.","journal-title":"J Biomed Inform"},{"key":"33_CR26","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1093\/bib\/6.3.239","volume":"6","author":"I Spasi\u0107","year":"2005","unstructured":"Spasi\u0107 I, Ananiadou S, McNaught J, Kumar A. Text mining and ontologies in biomedicine: making sense of raw text. Brief Bioinform. 2005;6:239\u201351.","journal-title":"Brief Bioinform"},{"key":"33_CR27","doi-asserted-by":"publisher","first-page":"615","DOI":"10.1016\/j.jbi.2013.04.009","volume":"46","author":"K Button","year":"2013","unstructured":"Button K, van Deursen RW, Soldatova L, Spasi\u0107 I. TRAK ontology: Defining standard care for the rehabilitation of knee conditions. J Biomed Inform. 2013;46:615\u201325.","journal-title":"J Biomed Inform"},{"key":"33_CR28","volume-title":"Introducing JSON","author":"D Crockford","year":"2009","unstructured":"Crockford D. Introducing JSON. 2009. http:\/\/json.org\/."},{"key":"33_CR29","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1145\/234173.234209","volume":"39","author":"J Cowie","year":"1996","unstructured":"Cowie J, Lehnert W. Information extraction. Commun ACM. 1996;39:80\u201391.","journal-title":"Commun ACM"},{"key":"33_CR30","unstructured":"Jacobson I, Booch G, Rumbaugh J. The Unified Software Development Process. Boston, USA: Addison-Wesley Professional; 1999"},{"key":"33_CR31","volume-title":"MR Knee","author":"Radiological Society of North America","year":"2012","unstructured":"Radiological Society of North America. MR Knee. 2012. http:\/\/www.radreport.org\/template\/0000057."},{"key":"33_CR32","first-page":"102","volume-title":"The 3th Conference of the European Chapter of the Association for Computational Linguistics; Avignon, France","author":"P Stenetorp","year":"2012","unstructured":"Stenetorp P, Pyysalo S, Topi\u0107 G, Ohta T, Ananiadou S, Tsujii J. BRAT: a web-based tool for NLP-assisted text annotation. In: The 3th Conference of the European Chapter of the Association for Computational Linguistics; Avignon, France. 2012. p. 102\u20137."},{"key":"33_CR33","volume-title":"Read Codes","author":"Health & Social Care Information Centre","year":"2015","unstructured":"Health & Social Care Information Centre. Read Codes. 2015. http:\/\/systems.hscic.gov.uk\/data\/uktc\/readcodes."},{"key":"33_CR34","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1111\/j.1365-2125.2009.03537.x","volume":"69","author":"E Herrett","year":"2010","unstructured":"Herrett E, Thomas SL, Schoonen WM, Smeeth L, Hall AJ. Validation and validity of diagnoses in the General Practice Research Database: A systematic review. Br J Clin Pharmacol. 2010;69:4\u201314.","journal-title":"Br J Clin Pharmacol"},{"key":"33_CR35","doi-asserted-by":"publisher","first-page":"2198","DOI":"10.1093\/bioinformatics\/btm112","volume":"23","author":"J Day-Richter","year":"2007","unstructured":"Day-Richter J, Harris MA, Haendel M, The Gene Ontology OBO-Edit Working Group, Lewis S. OBO-Edit - an ontology editor for biologists. Bioinformatics. 2007;23:2198\u2013200.","journal-title":"Bioinformatics"},{"key":"33_CR36","doi-asserted-by":"publisher","first-page":"W541","DOI":"10.1093\/nar\/gkr469","volume":"39","author":"P Whetzel","year":"2011","unstructured":"Whetzel P, Noy N, Shah N, Alexander P, Nyulas C, Tudorache T, et al. BioPortal: enhanced functionality via new Web services from the National Center for Biomedical Ontology to access and use ontologies in software applications. Nucleic Acids Res. 2011;39:W541\u20135.","journal-title":"Nucleic Acids Res"},{"key":"33_CR37","doi-asserted-by":"publisher","first-page":"478","DOI":"10.1016\/j.jbi.2003.11.007","volume":"36","author":"C Rosse","year":"2003","unstructured":"Rosse C, Mejino JJ. A reference ontology for biomedical informatics: the Foundational Model of Anatomy. J Biomed Inform. 2003;36:478\u2013500.","journal-title":"J Biomed Inform"},{"key":"33_CR38","doi-asserted-by":"publisher","first-page":"D267","DOI":"10.1093\/nar\/gkh061","volume":"32","author":"O Bodenreider","year":"2004","unstructured":"Bodenreider O. The Unified Medical Language System (UMLS): integrating biomedical terminology. Nucleic Acids Res. 2004;32:D267\u201370.","journal-title":"Nucleic Acids Res"},{"key":"33_CR39","first-page":"17","volume-title":"Proceedings of the American Medical Informatics Association","author":"AR Aronson","year":"2001","unstructured":"Aronson AR. Effective mapping of biomedical text to the UMLS Metathesaurus: the MetaMap program. In: Proceedings of the American Medical Informatics Association. 2001. p. 17\u201321."},{"key":"33_CR40","doi-asserted-by":"publisher","first-page":"661","DOI":"10.1137\/070710111","volume":"51","author":"A Clauset","year":"2009","unstructured":"Clauset A, Shalizi CR, Newman MEJ. Power-law distributions in empirical data. SIAM Rev. 2009;51:661\u2013703.","journal-title":"SIAM Rev"},{"key":"33_CR41","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1016\/0895-7177(94)90041-8","volume":"19","author":"Y-S Chen","year":"1994","unstructured":"Chen Y-S, Chong PP, Tong MY. Mathematical and computer modelling of the Pareto principle. Math Comput Model. 1994;19:61\u201380.","journal-title":"Math Comput Model"},{"key":"33_CR42","first-page":"580","volume-title":"Proceedings of the AMIA Annual Fall Symposium","author":"WR Hersh","year":"1997","unstructured":"Hersh WR, Campbell EM, Malveau SE. Assessing the feasibility of large-scale natural language processing in a corpus of ordinary medical records: a lexical analysis. In: Proceedings of the AMIA Annual Fall Symposium. 1997. p. 580\u20134."},{"key":"33_CR43","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1186\/2041-1480-4-27","volume":"4","author":"I Spasi\u0107","year":"2013","unstructured":"Spasi\u0107 I, Greenwood M, Preece A, Francis N, Elwyn G. FlexiTerm: A flexible term recognition method. J Biomed Semantics. 2013;4:27.","journal-title":"J Biomed Semantics"},{"key":"33_CR44","volume-title":"Terminology Services","author":"UMLS","year":"2015","unstructured":"UMLS. Terminology Services. 2015. https:\/\/uts.nlm.nih.gov\/."},{"key":"33_CR45","volume-title":"MEDCIN Source Information","author":"UMLS","year":"2014","unstructured":"UMLS. MEDCIN Source Information. 2014. http:\/\/www.nlm.nih.gov\/research\/umls\/sourcereleasedocs\/current\/MEDCIN\/."},{"key":"33_CR46","first-page":"75","volume-title":"Proceedings of the AMIA Annual Symposium","author":"SH Brown","year":"2007","unstructured":"Brown SH, Rosenbloom ST, Bauer BA, Wahner-Roedler D, Froehling DA, Bailey KR, et al. Direct comparison of MEDCIN and SNOMED CT for representation of a general medical evaluation template. In: Proceedings of the AMIA Annual Symposium. 2007. p. 75\u20139."},{"key":"33_CR47","volume-title":"BioPortal","author":"National Center for Biomedical Ontology","year":"2013","unstructured":"National Center for Biomedical Ontology. BioPortal. 2013. http:\/\/bioportal.bioontology.org\/."},{"key":"33_CR48","doi-asserted-by":"publisher","first-page":"1595","DOI":"10.1148\/rg.266065168","volume":"26","author":"CP Langlotz","year":"2006","unstructured":"Langlotz CP. RadLex: a new method for indexing online educational materials. Radiographics. 2006;26:1595\u20137.","journal-title":"Radiographics"},{"key":"33_CR49","first-page":"1593","volume-title":"Proceedings of the AMIA Annual Symposium; Washington, DC","author":"M Yetisgen-Yildiz","year":"2011","unstructured":"Yetisgen-Yildiz M, Gunn ML, Xia F, Payne TH. Automatic identification of critical follow-up recommendation sentences in radiology reports. In: Proceedings of the AMIA Annual Symposium; Washington, DC. 2011. p. 1593\u2013602."},{"key":"33_CR50","unstructured":"MongoDB. 2015: https:\/\/www.mongodb.org\/."},{"key":"33_CR51","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1186\/1471-2105-15-59","volume":"15","author":"C Funk","year":"2014","unstructured":"Funk C, Baumgartner W, Garcia B, Roeder C, Bada M, Cohen KB, et al. Large-scale biomedical concept recognition: an evaluation of current automatic annotators and their parameters. BMC Bioinformatics. 2014;15:59.","journal-title":"BMC Bioinformatics"},{"key":"33_CR52","doi-asserted-by":"publisher","first-page":"455","DOI":"10.1147\/sj.433.0455","volume":"43","author":"D Ferrucci","year":"2004","unstructured":"Ferrucci D, Lally A. Building an example application with the unstructured information management architecture. IBM Syst J. 2004;43:455\u201375.","journal-title":"IBM Syst J"},{"key":"33_CR53","doi-asserted-by":"publisher","first-page":"S2","DOI":"10.1186\/1752-0509-7-S3-S2","volume":"7","author":"C Wu","year":"2013","unstructured":"Wu C, Schwartz J-M, Nenadi\u0107 G. PathNER: a tool for systematic identification of biological pathway mentions in the literature. BMC Syst Biol. 2013;7:S2.","journal-title":"BMC Syst Biol"},{"key":"33_CR54","first-page":"73","volume-title":"Proceedings of the IJCAI-2003 Workshop on Information Integration on the Web","author":"WW Cohen","year":"2003","unstructured":"Cohen WW, Ravikumar P, Fienberg SE. A comparison of string distance metrics for name-matching tasks. In: Kambhampati S, Knoblock CA, editors. Proceedings of the IJCAI-2003 Workshop on Information Integration on the Web. 2003. p. 73\u20138."},{"key":"33_CR55","doi-asserted-by":"publisher","first-page":"513","DOI":"10.1016\/0306-4573(88)90021-0","volume":"24","author":"G Salton","year":"1988","unstructured":"Salton G, Buckley C. Term-weighting approaches in automatic text retrieval. Info Process Manag. 1988;24:513\u201323.","journal-title":"Info Process Manag"},{"key":"33_CR56","first-page":"354","volume-title":"Proceedings of the Section on Survey Research Methods (American Statistical Association)","author":"WE Winkler","year":"1990","unstructured":"Winkler WE. String comparator metrics and enhanced decision rules in the Fellegi-Sunter model of record linkage. In: Proceedings of the Section on Survey Research Methods (American Statistical Association). 1990. p. 354\u20139."},{"key":"33_CR57","doi-asserted-by":"publisher","first-page":"2768","DOI":"10.1093\/bioinformatics\/btm393","volume":"23","author":"Y Tsuruoka","year":"2007","unstructured":"Tsuruoka Y, McNaught J, Tsujii J, Ananiadou S. Learning string similarity measures for gene\/protein name dictionary look-up using logistic regression. Bioinformatics. 2007;23:2768\u201374.","journal-title":"Bioinformatics"},{"key":"33_CR58","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1097\/JSM.0b013e318059b536","volume":"17","author":"K Rae","year":"2007","unstructured":"Rae K, Orchard J. The Orchard Sports Injury Classification System (OSICS) version 10. Clin J Sport Med. 2007;17:201\u20134.","journal-title":"Clin J Sport Med"},{"key":"33_CR59","doi-asserted-by":"publisher","first-page":"552","DOI":"10.1136\/bjsports-2012-091219","volume":"48","author":"C Finch","year":"2012","unstructured":"Finch C, Orchard J, Twomey D, Saad Saleem M, Ekegren C, Lloyd D, et al. Coding OSICS sports injury diagnoses in epidemiological studies: does the background of the coder matter? Br J Sports Med. 2012;48:552\u20136.","journal-title":"Br J Sports Med"},{"key":"33_CR60","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1017\/S1351324900000048","volume":"1","author":"JS Justeson","year":"1995","unstructured":"Justeson JS, Katz SM. Technical terminology: some linguistic properties and an algorithm for identification in text. Nat Lang Eng. 1995;1:9\u201327.","journal-title":"Nat Lang Eng"},{"key":"33_CR61","unstructured":"MinorThird. 2015: http:\/\/minorthird.sourceforge.net\/."},{"key":"33_CR62","doi-asserted-by":"publisher","first-page":"218","DOI":"10.1186\/1471-2105-12-218","volume":"12","author":"T Adamusiak","year":"2011","unstructured":"Adamusiak T, Burdett T, Kurbatova N, Velde KJ, Abeygunawardena N, Antonakaki D, et al. OntoCAT - simple ontology search and integration in Java, R and REST\/JavaScript. BMC Bioinformatics. 2011;12:218.","journal-title":"BMC Bioinformatics"},{"key":"33_CR63","doi-asserted-by":"publisher","first-page":"378","DOI":"10.1037\/h0031619","volume":"76","author":"JL Fleiss","year":"1971","unstructured":"Fleiss JL. Measuring nominal scale agreement among many raters. Psychol Bull. 1971;76:378\u201382.","journal-title":"Psychol Bull"},{"key":"33_CR64","doi-asserted-by":"publisher","first-page":"555","DOI":"10.1162\/coli.07-034-R2","volume":"34","author":"R Artstein","year":"2008","unstructured":"Artstein R, Poesio M. Inter-coder agreement for computational linguistics. Computational Linguistics. 2008;34:555\u201396.","journal-title":"Computational Linguistics"},{"key":"33_CR65","volume-title":"Inter-rater agreement with multiple raters and variable","author":"J Geertzen","year":"2015","unstructured":"Geertzen J. Inter-rater agreement with multiple raters and variable. 2015. https:\/\/mlnl.net\/jg\/software\/ira\/."},{"key":"33_CR66","doi-asserted-by":"publisher","first-page":"159","DOI":"10.2307\/2529310","volume":"33","author":"JR Landis","year":"1977","unstructured":"Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33:159\u201374.","journal-title":"Biometrics"}],"container-title":["Journal of Biomedical Semantics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13326-015-0033-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13326-015-0033-1","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s13326-015-0033-1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13326-015-0033-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T00:20:50Z","timestamp":1790036450000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1186\/s13326-015-0033-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,9,7]]},"references-count":66,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2015,12]]}},"alternative-id":["33"],"URL":"https:\/\/doi.org\/10.1186\/s13326-015-0033-1","relation":{},"ISSN":["2041-1480"],"issn-type":[{"value":"2041-1480","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,9,7]]},"assertion":[{"value":"27 March 2015","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 August 2015","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 September 2015","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"34"}}