{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T10:38:43Z","timestamp":1776335923348,"version":"3.51.2"},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"S2","license":[{"start":{"date-parts":[[2015,6,15]],"date-time":"2015-06-15T00:00:00Z","timestamp":1434326400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Med Inform Decis Mak"],"published-print":{"date-parts":[[2015,12]]},"DOI":"10.1186\/1472-6947-15-s2-s6","type":"journal-article","created":{"date-parts":[[2015,6,18]],"date-time":"2015-06-18T15:50:14Z","timestamp":1434642614000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":36,"title":["Exploring Spanish health social media for detecting drug effects"],"prefix":"10.1186","volume":"15","author":[{"given":"Isabel","family":"Segura-Bedmar","sequence":"first","affiliation":[]},{"given":"Paloma","family":"Mart\u00ednez","sequence":"additional","affiliation":[]},{"given":"Ricardo","family":"Revert","sequence":"additional","affiliation":[]},{"given":"Juli\u00e1n","family":"Moreno-Schneider","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2015,6,15]]},"reference":[{"issue":"4","key":"914_CR1","doi-asserted-by":"publisher","first-page":"573","DOI":"10.1111\/j.1365-2125.2007.03064.x","volume":"65","author":"K Wester","year":"2008","unstructured":"Wester K, J\u00f6nsson AK, Spigset O, Druid H, Staffan H: Incidence of fatal adverse drug reactions: a population based study. Brit J Clin Pharmaco. 2008, 65 (4): 573-579. 10.1111\/j.1365-2125.2007.03064.x.","journal-title":"Brit J Clin Pharmaco"},{"issue":"5","key":"914_CR2","doi-asserted-by":"publisher","first-page":"601","DOI":"10.1592\/phco.26.5.601","volume":"26","author":"CA Bond","year":"2006","unstructured":"Bond CA, Raehl CL: Adverse drug reactions in United States hospitals. Pharmacotherapy. 2006, 26 (5): 601-608. 10.1592\/phco.26.5.601.","journal-title":"Pharmacotherapy"},{"issue":"2","key":"914_CR3","doi-asserted-by":"publisher","first-page":"161","DOI":"10.2165\/00002018-200629020-00006","volume":"29","author":"CS van Der Hooft","year":"2006","unstructured":"van Der Hooft CS, Sturkenboom MCJM, van Grootheest K, Kingma HJ, Stricker BHCh: Adverse drug reaction-related hospitalisations. Drug Saf. 2006, 29 (2): 161-168. 10.2165\/00002018-200629020-00006.","journal-title":"Drug Saf"},{"issue":"2","key":"914_CR4","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1197\/jamia.M1074","volume":"10","author":"DW Bates","year":"2003","unstructured":"Bates DW, Evans RC, Murff H, Stetson PD, Pizziferri L, Hripcsak G: Detecting adverse events using information technology. J Am Med Inform Assoc. 2003, 10 (2): 115-128. 10.1197\/jamia.M1074.","journal-title":"J Am Med Inform Assoc"},{"issue":"17","key":"914_CR5","doi-asserted-by":"publisher","first-page":"1700","DOI":"10.1056\/NEJMp078057","volume":"356","author":"M McClellan","year":"2007","unstructured":"McClellan M: Drug Safety Reform at the FDA-Pendulum Swing or Systematic Improvement?. N Engl J Med. 2007, 356 (17): 1700-1702. 10.1056\/NEJMp078057.","journal-title":"N Engl J Med"},{"issue":"1","key":"914_CR6","first-page":"41","volume":"29","author":"M Rawlins","year":"1995","unstructured":"Rawlins M: Pharmacovigilance: paradise lost, regained or postponed? The William Withering Lecture 1994. J R Coll Physicians Lond. 1995, 29 (1): 41-49.","journal-title":"J R Coll Physicians Lond"},{"key":"914_CR7","volume-title":"Health Action International (HAI)","author":"A Herxheimer","year":"2010","unstructured":"Herxheimer A, Crombag MR, Alves TL: Direct patient reporting of adverse drug reactions. A twelve-country survey & literature review. Health Action International (HAI). 2010, Europe Paper Series Reference 01-2010\/01"},{"issue":"3","key":"914_CR8","doi-asserted-by":"publisher","first-page":"160","DOI":"10.1089\/big.2013.0020","volume":"1","author":"Hill Shawndra","year":"2013","unstructured":"Shawndra Hill, Raina Merchant, Lile Ungar: Lessons Learned About Public Health from Online Crowd Surveillance. Big Data. 2013, 1 (3): 160-167. 10.1089\/big.2013.0020.","journal-title":"Big Data"},{"issue":"5","key":"914_CR9","doi-asserted-by":"publisher","first-page":"879","DOI":"10.1016\/j.jbi.2012.04.004","volume":"45","author":"EM Van Mulligen","year":"2012","unstructured":"Van Mulligen EM, Fourrier-Reglat A, Gurwitz D, Molokhia M, Nieto A, Trifiro G, Furlong LI: The EU-ADR corpus: Annotated drugs, diseases, targets, and their relationships. Journal of biomedical informatics. 2012, 45 (5): 879-884. 10.1016\/j.jbi.2012.04.004.","journal-title":"Journal of biomedical informatics"},{"issue":"5","key":"914_CR10","doi-asserted-by":"publisher","first-page":"885","DOI":"10.1016\/j.jbi.2012.04.008","volume":"45","author":"H Gurulingappa","year":"2012","unstructured":"Gurulingappa H, Rajput AM, Roberts A, Fluck J, Hofmann-Apitius M, Toldo L: Development of a benchmark corpus to support the automatic extraction of drug-related adverse effects from medical case reports. Journal of biomedical informatics. 2012, 45 (5): 885-892. 10.1016\/j.jbi.2012.04.008.","journal-title":"Journal of biomedical informatics"},{"issue":"11","key":"914_CR11","doi-asserted-by":"publisher","first-page":"1189","DOI":"10.1002\/pds.3493","volume":"22","author":"H Gurulingappa","year":"2013","unstructured":"Gurulingappa H, Toldo L, Mateen-Rajput A, Kors JA, Taweel A, Tayrouz Y: Automatic detection of adverse events to predict drug label changes using text and data mining techniques. Pharmacoepidemiol Drug Saf. 2013, 22 (11): 1189-1194. 10.1002\/pds.3493.","journal-title":"Pharmacoepidemiol Drug Saf"},{"issue":"1","key":"914_CR12","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1186\/1472-6947-13-53","volume":"13","author":"Q Li","year":"2013","unstructured":"Li Q, Deleger L, Lingren T, Zhai H, Kaiser M, Stoutenborough L, Jegga AG, Cohen KB, Solti I: Mining FDA drug labels for medical conditions. BMC Med Inform and Decis Mak. 2013, 13 (1): 53-10.1186\/1472-6947-13-53.","journal-title":"BMC Med Inform and Decis Mak"},{"issue":"343","key":"914_CR13","first-page":"1","volume":"6","author":"M Kuhn","year":"2010","unstructured":"Kuhn M, Campillos M, Letunic I, Jensen LJ, Bork P: A side effect resource to capture phenotypic effects of drugs. Mol Syst Biol. 2010, 6 (343): 1-6.","journal-title":"Mol Syst Biol"},{"issue":"1","key":"914_CR14","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1186\/1471-2105-14-181","volume":"14","author":"R Xu","year":"2013","unstructured":"Xu R, Wang Q: Large-scale extraction of accurate drug-disease treatment pairs from biomedical literature for drug repurposing. BMC Bioinformatics. 2013, 14 (1): 181-10.1186\/1471-2105-14-181.","journal-title":"BMC Bioinformatics"},{"issue":"1","key":"914_CR15","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1186\/2041-1480-3-15","volume":"3","author":"H Gurulingappa","year":"2012","unstructured":"Gurulingappa H, Mateen-Rajput A, Toldo L: Extraction of potential adverse drug events from medical case reports. Journal of Biomed Semantics. 2012, 3 (1): 15-10.1186\/2041-1480-3-15.","journal-title":"Journal of Biomed Semantics"},{"key":"914_CR16","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-3-642-02976-9_1","volume-title":"Artificial Intelligence in Medicine","author":"C Friedman","year":"2009","unstructured":"Friedman C: Discovering novel adverse drug events using natural language processing and mining of the electronic health record. Artificial Intelligence in Medicine. 2009, LNAI, 5651: 1-5."},{"issue":"Suppl 1","key":"914_CR17","doi-asserted-by":"publisher","first-page":"i144","DOI":"10.1136\/amiajnl-2011-000351","volume":"18","author":"S Sohn","year":"2011","unstructured":"Sohn S, Kocher JPA, Chute CG, Savova GK: Drug side effect extraction from clinical narratives of psychiatry and psychology patients. J Am Med Inform Assoc. 2011, 18 (Suppl 1): i144-i149.","journal-title":"J Am Med Inform Assoc"},{"key":"914_CR18","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1007\/978-3-642-40140-4_12","volume":"146","author":"F Bouillot","year":"2013","unstructured":"Bouillot F, Hai PN, B\u00e9chet N, Bringay S, Ienco D, Matwin S, Poncelet P, Roche M, Teisseire M: How to Extract Relevant Knowledge from Tweets?. Information Search, Integration and Personalization CCIS. 2013, 146: 111-120. 10.1007\/978-3-642-40140-4_12.","journal-title":"Information Search, Integration and Personalization CCIS"},{"key":"914_CR19","doi-asserted-by":"publisher","first-page":"59","DOI":"10.17562\/PB-48-8","volume":"48","author":"M Neunerdt","year":"2013","unstructured":"Neunerdt M, Reyer M, Mathar R: A POS Tagger for Social Media Texts trained on Web Comments. Polibits. 2013, 48: 59-66.","journal-title":"Polibits"},{"key":"914_CR20","first-page":"490","volume":"2","author":"S Moreira","year":"2013","unstructured":"Moreira S, Filgueiras J, Martins B, Couto F, Silva MJ: REACTION: A naive machine learning approach for sentiment classification. In Proceedings of SEM. 2013, 2: 490-494.","journal-title":"In Proceedings of SEM"},{"key":"914_CR21","first-page":"120","volume-title":"In Proceedings WASSA","author":"A Balahur","year":"2013","unstructured":"Balahur A: Sentiment Analysis in Social Media Texts. In Proceedings WASSA. 2013, 120-128."},{"issue":"65","key":"914_CR22","first-page":"341","volume":"3206","author":"I Segura-Bedmar","year":"2013","unstructured":"Segura-Bedmar I, Mart\u00ednez P, Herrero-Zazo M: SemEval-2013 Task 9: Extraction of Drug-Drug Interactions from Biomedical Texts. Proceedings of DDIExtraction. 2013, 3206 (65): 341-351.","journal-title":"Proceedings of DDIExtraction"},{"key":"914_CR23","first-page":"2","volume":"2","author":"M Krallinger","year":"2013","unstructured":"Krallinger M, Leitner F, Rabal O, V\u00e1zquez M, Oyarzabal J, Valencia A: Overview of the chemical compound and drug name recognition (CHEMDNER) task. BioCreative Challenge Evaluation Workshop. 2013, 2: 2-33.","journal-title":"BioCreative Challenge Evaluation Workshop"},{"issue":"5","key":"914_CR24","doi-asserted-by":"publisher","first-page":"514","DOI":"10.1136\/jamia.2010.003947","volume":"17","author":"O Uzuner","year":"2010","unstructured":"Uzuner O, Solti I, Cadag E: Extracting medication information from clinical text. J Am Med Inform Assoc. 2010, 17 (5): 514-518. 10.1136\/jamia.2010.003947.","journal-title":"J Am Med Inform Assoc"},{"key":"914_CR25","first-page":"117","volume-title":"In Proceedings of BioNLP","author":"R Leaman","year":"2010","unstructured":"Leaman R, Wojtulewicz L, Sullivan R, Skariah A, Yang J, Gonz\u00e1lez G: Towards internet-age pharmacovigilance: extracting adverse drug reactions from user posts to health-related social networks. In Proceedings of BioNLP. 2010, 117-125."},{"key":"914_CR26","first-page":"1019","volume-title":"Proceedings of AMIA Annual Symposium","author":"A Nikfarjam","year":"2011","unstructured":"Nikfarjam A, Gonz\u00e1lez GH: Pattern mining for extraction of mentions of adverse drug reactions from user comments. Proceedings of AMIA Annual Symposium. 2011, 1019-1026."},{"key":"914_CR27","first-page":"487","volume":"1215","author":"R Agrawal","year":"1994","unstructured":"Agrawal R, Srikant R: Fast algorithms for mining association rules. Proc 20th Int Conf Very Large DataBases. 1994, 1215: 487-499.","journal-title":"Proc 20th Int Conf Very Large DataBases"},{"issue":"6","key":"914_CR28","doi-asserted-by":"publisher","first-page":"989","DOI":"10.1016\/j.jbi.2011.07.005","volume":"44","author":"A Benton","year":"2011","unstructured":"Benton A, Ungar L, Hill S, Hennessy S, Mao J, Chung A, Leonarda CH, Holmes JH: Identifying potential adverse effects using the web: A new approach to medical hypothesis generation. J Biomed Inform. 2011, 44 (6): 989-996. 10.1016\/j.jbi.2011.07.005.","journal-title":"J Biomed Inform"},{"issue":"1","key":"914_CR29","doi-asserted-by":"publisher","first-page":"87","DOI":"10.2307\/2340521","volume":"85","author":"RA Fisher","year":"1922","unstructured":"Fisher RA: On the interpretation of \u03c72 from contingency tables, and the calculation of P. Journal of the Royal Statistical Society. 1922, 85 (1): 87-94. 10.2307\/2340521.","journal-title":"Journal of the Royal Statistical Society"},{"key":"914_CR30","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1145\/2389707.2389713","volume-title":"In Proceedings of SHB","author":"J Bian","year":"2012","unstructured":"Bian J, Topaloglu U, Yu F: Towards large-scale twitter mining for drug-related adverse events. In Proceedings of SHB. 2012, 25-32."},{"issue":"3","key":"914_CR31","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1136\/jamia.2009.002733","volume":"17","author":"AR Aronson","year":"2010","unstructured":"Aronson AR, Lang FM: An overview of MetaMap: historical perspective and recent advances. J Am Med Inform Assoc. 2010, 17 (3): 229-236. 10.1136\/jamia.2009.002733.","journal-title":"J Am Med Inform Assoc"},{"key":"914_CR32","first-page":"106","volume-title":"Proceedings of LOUHI","author":"I Segura-Bedmar","year":"2014","unstructured":"Segura-Bedmar I, Revert R, Mart\u00ednez P: Detecting drugs and adverse events from Spanish social media streams. Proceedings of LOUHI. 2014, ACL, 106-115."},{"key":"914_CR33","first-page":"98","volume-title":"Proceedings of BioNLP","author":"I Segura-Bedmar","year":"2014","unstructured":"Segura-Bedmar I, Pe\u00f1a-Gonz\u00e1lez S, Mart\u00ednez P: Extracting drug indications and adverse drug reactions from Spanish health social media. Proceedings of BioNLP. 2014, 98-106."},{"key":"914_CR34","first-page":"1003","volume":"2","author":"M Mintz","year":"2009","unstructured":"Mintz M, Bills S, Snow R, Jurafsky D: Distant supervision for relation extraction without labeled data. Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP. 2009, 2: 1003-1011.","journal-title":"Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP"},{"key":"914_CR35","first-page":"98","volume-title":"Proceedings of EACL","author":"C Giuliano","year":"2006","unstructured":"Giuliano C, Lavelli A, Romano L: Exploiting Shallow Linguistic Information for Relation Extraction from Biomedical Literature. Proceedings of EACL. 2006, 98-113."},{"key":"914_CR36","first-page":"2","volume":"5","author":"C Giuliano","year":"2007","unstructured":"Giuliano C, Lavelli A, Romano L: Relation extraction and the influence of automatic named-entity recognition. ACM Trans Speech Lang Process (TSLP). 2007, 5: 2-","journal-title":"ACM Trans Speech Lang Process (TSLP)"},{"key":"914_CR37","volume-title":"Proceedigns of NIPS","author":"R Bunescu","year":"2005","unstructured":"Bunescu R, Mooney RJ: Subsequence kernels for relation extraction. Proceedigns of NIPS. 2005"},{"key":"914_CR38","volume-title":"Cambridge University Press","author":"J Shawe-Taylor","year":"2004","unstructured":"Shawe-Taylor J, Cristianini N: Kernel methods for pattern analysis. Cambridge University Press. 2004"},{"key":"914_CR39","first-page":"77","volume-title":"Proceedings of ISMB","author":"M Craven","year":"1999","unstructured":"Craven M, Kumlien J: Constructing biological knowledge bases by extracting information from text sources. Proceedings of ISMB. 1999, 77-86."},{"key":"914_CR40","first-page":"777","volume-title":"Proceedings of HLT-NAACL","author":"B Min","year":"2013","unstructured":"Min B, Grishman R, Wan L, Wang C, Gondek D: Distant Supervision for Relation Extraction with an Incomplete Knowledge Base. Proceedings of HLT-NAACL. 2013, 777-782."}],"container-title":["BMC Medical Informatics and Decision Making"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/1472-6947-15-S2-S6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/1472-6947-15-S2-S6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/1472-6947-15-S2-S6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,1,23]],"date-time":"2019-01-23T02:48:36Z","timestamp":1548211716000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcmedinformdecismak.biomedcentral.com\/articles\/10.1186\/1472-6947-15-S2-S6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,6,15]]},"references-count":40,"journal-issue":{"issue":"S2","published-print":{"date-parts":[[2015,12]]}},"alternative-id":["914"],"URL":"https:\/\/doi.org\/10.1186\/1472-6947-15-s2-s6","relation":{},"ISSN":["1472-6947"],"issn-type":[{"value":"1472-6947","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,6,15]]},"assertion":[{"value":"15 June 2015","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"S6"}}