{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T08:48:11Z","timestamp":1784105291823,"version":"3.55.0"},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2014,1,15]],"date-time":"2014-01-15T00:00:00Z","timestamp":1389744000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/2.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2014,12]]},"DOI":"10.1186\/1471-2105-15-17","type":"journal-article","created":{"date-parts":[[2014,1,15]],"date-time":"2014-01-15T09:05:43Z","timestamp":1389776743000},"source":"Crossref","is-referenced-by-count":69,"title":["Large-scale combining signals from both biomedical literature and the FDA Adverse Event Reporting System (FAERS) to improve post-marketing drug safety signal detection"],"prefix":"10.1186","volume":"15","author":[{"given":"Rong","family":"Xu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"QuanQiu","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2014,1,15]]},"reference":[{"issue":"6","key":"6285_CR1","doi-asserted-by":"publisher","first-page":"483","DOI":"10.1002\/pds.677","volume":"10","author":"SJW Evans","year":"2001","unstructured":"Evans SJW, Waller PC, Davis S: Use of proportional reporting ratios (PRRs) for signal generation from spontaneous adverse drug reaction reports. Pharmacoepidemiol Drug Saf. 2001, 10 (6): 483-486. 10.1002\/pds.677.","journal-title":"Pharmacoepidemiol Drug Saf"},{"issue":"6","key":"6285_CR2","doi-asserted-by":"publisher","first-page":"1010","DOI":"10.1038\/clpt.2012.50","volume":"91","author":"R Harpaz","year":"2012","unstructured":"Harpaz R, DuMouchel W, Shah NH, Madigan D, Ryan P, Friedman C: Novel data-mining methodologies for adverse drug event discovery and analysis. Clin Pharmacol Ther. 2012, 91 (6): 1010-1021. 10.1038\/clpt.2012.50.","journal-title":"Clin Pharmacol Ther"},{"issue":"6","key":"6285_CR3","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1002\/pds.1742","volume":"18","author":"A Bate","year":"2009","unstructured":"Bate A, Evans SJW: Quantitative signal detection using spontaneous ADR reporting. Pharmacoepidemiol Drug Saf. 2009, 18 (6): 427-436. 10.1002\/pds.1742.","journal-title":"Pharmacoepidemiol Drug Saf"},{"issue":"3","key":"6285_CR4","doi-asserted-by":"publisher","first-page":"413","DOI":"10.1136\/amiajnl-2012-000930","volume":"20","author":"R Harpaz","year":"2013","unstructured":"Harpaz R, Vilar S, DuMouchel W, Salmasian H, Haerian K, Shah NH, Friedman C: Combing signals from spontaneous reports and electronic health records for detection of adverse drug reactions. J Am Med Inform Assoc. 2013, 20 (3): 413-419. 10.1136\/amiajnl-2012-000930.","journal-title":"J Am Med Inform Assoc"},{"key":"6285_CR5","doi-asserted-by":"crossref","unstructured":"Xu R, Wang Q: Automatic signal prioritizing and filtering approaches in detecting post-marketing cardiovascular events associated with targeted cancer drugs from the FDA Adverse Event Reporting System (FAERS). J Biomed Inform. (in press),","DOI":"10.1016\/j.jbi.2013.10.008"},{"issue":"4","key":"6285_CR6","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1002\/pds.1323","volume":"16","author":"WP Stephenson","year":"2007","unstructured":"Stephenson WP, Hauben M: Data mining for signals in spontaneous reporting databases: proceed with caution. Pharmacoepidemiol Drug Saf. 2007, 16 (4): 359-365. 10.1002\/pds.1323.","journal-title":"Pharmacoepidemiol Drug Saf"},{"issue":"15","key":"6285_CR7","doi-asserted-by":"publisher","first-page":"1200","DOI":"10.1001\/jama.279.15.1200","volume":"279","author":"J Lazarou","year":"1998","unstructured":"Lazarou J, Pomeranz BH, Corey PN: Incidence of adverse drug reactions in hospitalized patients. JAMA: J Am Med Assoc. 1998, 279 (15): 1200-1205. 10.1001\/jama.279.15.1200.","journal-title":"JAMA: J Am Med Assoc"},{"issue":"5","key":"6285_CR8","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1097\/00006254-199705000-00016","volume":"52","author":"DC Classen","year":"1997","unstructured":"Classen DC, Pestonik SL, Evans RS, Lloyd JF, Burke JP: Adverse drug events in hospitalized patients: excess length of stay, extra costs, and attributable mortality. Obstet Gynecol Surv. 1997, 52 (5): 291-292. 10.1097\/00006254-199705000-00016.","journal-title":"Obstet Gynecol Surv"},{"issue":"1","key":"6285_CR9","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1046\/j.1525-1497.2003.20130.x","volume":"18","author":"SR Ahmad","year":"2003","unstructured":"Ahmad SR: Adverse drug event monitoring at the food and drug administration. J Gen Intern Med. 2003, 18 (1): 57-60. 10.1046\/j.1525-1497.2003.20130.x.","journal-title":"J Gen Intern Med"},{"issue":"7","key":"6285_CR10","doi-asserted-by":"publisher","first-page":"645","DOI":"10.1056\/NEJMp0905338","volume":"361","author":"R Platt","year":"2009","unstructured":"Platt R, Wilson M, Chan KA, Benner JS, Marchibroda J, McClellan M: The new sentinel network: improving the evidence of medical-product safety. N Engl J Med. 2009, 361 (7): 645-647. 10.1056\/NEJMp0905338.","journal-title":"N Engl J Med"},{"key":"6285_CR11","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, Berlin Heidelberg: Springer, 1-5."},{"issue":"3","key":"6285_CR12","doi-asserted-by":"publisher","first-page":"420","DOI":"10.1136\/amiajnl-2012-001119","volume":"20","author":"M Liu","year":"2013","unstructured":"Liu M, Hinz ERM, Matheny ME, Denny JC, Schildcrout JS, Miller RA, Xu H: Comparative analysis of pharmacovigilance methods in the detection of adverse drug reactions using electronic medical records. J Am Med Inform Assoc. 2013, 20 (3): 420-426. 10.1136\/amiajnl-2012-001119.","journal-title":"J Am Med Inform Assoc"},{"key":"6285_CR13","first-page":"328","volume":"16","author":"X Wang","year":"2009","unstructured":"Wang X, Hripcsak G, Markatou M, Friedman C: Active computerized Pharmacovigilance using natural language processing, statistics, and electronic health records: a feasibility study. JAMIA. 2009, 16: 328-337.","journal-title":"JAMIA"},{"issue":"Suppl 1","key":"6285_CR14","doi-asserted-by":"publisher","first-page":"i144","DOI":"10.1136\/amiajnl-2011-000351","volume":"18","author":"S Sohn","year":"2011","unstructured":"Sohn S, Kocher JP, Chute C, Savova G: Drug side effect extraction from clinical narratives of psychiatry and psychology patients. J Am Med Inform Assoc. 2011, 18 (Suppl 1): i144-i149. 10.1136\/amiajnl-2011-000351.","journal-title":"J Am Med Inform Assoc"},{"key":"6285_CR15","first-page":"552","volume":"18","author":"LO Uzuner","year":"2011","unstructured":"Uzuner LO, South BR, Shen SD: 2010 i2b2\/VA challenge on concepts, assertions, and relations in clinical text. JAMIA. 2011, 18: 552-556.","journal-title":"JAMIA"},{"key":"6285_CR16","first-page":"117","volume-title":"Proceedings of the 2010 workshop on biomedical natural language processing","author":"R Leaman","year":"2010","unstructured":"Leaman R, Wojtulewicz L, Sullivan R, Skariah A, Yang J, Gonzalez G: Towards internet-age pharmacovigilance: extracting adverse drug reactions from user posts to health-related social networks. Proceedings of the 2010 workshop on biomedical natural language processing. 2010, Uppsala, Sweden: Association for Computational Linguistics, 117-125."},{"issue":"3","key":"6285_CR17","doi-asserted-by":"publisher","first-page":"404","DOI":"10.1136\/amiajnl-2012-001482","volume":"20","author":"RW White","year":"2013","unstructured":"White RW, Tatonetti NP, Shah NH, Altman RB, Horvitz E: Web-scale pharmacovigilance: listening to signals from the crowd. J Am Med Inform Assoc. 2013, 20 (3): 404-408. 10.1136\/amiajnl-2012-001482.","journal-title":"J Am Med Inform Assoc"},{"issue":"7","key":"6285_CR18","doi-asserted-by":"publisher","first-page":"527","DOI":"10.2165\/11532430-000000000-00000","volume":"33","author":"M Hauben","year":"2010","unstructured":"Hauben M, Noren GN: A decade of data mining and still counting. Drug Saf. 2010, 33 (7): 527-10.2165\/11532430-000000000-00000.","journal-title":"Drug Saf"},{"issue":"5","key":"6285_CR19","doi-asserted-by":"publisher","first-page":"668","DOI":"10.1136\/amiajnl-2011-000096","volume":"18","author":"KD Shetty","year":"2011","unstructured":"Shetty KD, Dalal SR: Using information mining of the medical literature to improve drug safety. J Am Med Inform Assoc. 2011, 18 (5): 668-674. 10.1136\/amiajnl-2011-000096.","journal-title":"J Am Med Inform Assoc"},{"issue":"1","key":"6285_CR20","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1186\/2041-1480-3-15","volume":"3","author":"H Gurulingappa","year":"2012","unstructured":"Gurulingappa H, Rajput A, Toldo L: Extraction of potential adverse drug events from medical case reports. J Biomed Semantics. 2012, 3 (1): 15-10.1186\/2041-1480-3-15.","journal-title":"J Biomed Semantics"},{"issue":"1","key":"6285_CR21","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1136\/amiajnl-2012-001584","volume":"21","author":"R Xu","year":"2014","unstructured":"Xu R, Wang Q: Toward creation of a cancer drug toxicity knowledge base: automatically extracting cancer drug-side effect relationships from the literature. J Am Med Inform Assoc. 2014, 21 (1): 90-96. 10.1136\/amiajnl-2012-001584.","journal-title":"J Am Med Inform Assoc"},{"issue":"125","key":"6285_CR22","doi-asserted-by":"crossref","first-page":"125ra31","DOI":"10.1126\/scitranslmed.3003377","volume":"4","author":"NP Tatonetti","year":"2012","unstructured":"Tatonetti NP, Patrick PY, Daneshjou R, Altman RB: Data-driven prediction of drug effects and interactions. Sci Transl Med. 2012, 4 (125): 125ra31-","journal-title":"Sci Transl Med"},{"key":"6285_CR23","unstructured":"The FDA Adverse Event Reporting System (FAERS). [ http:\/\/www.fda.gov\/Drugs\/GuidanceComplianceRegulatoryInformation\/Surveillance\/AdverseDrugEffects\/default.htm ],"},{"key":"6285_CR24","first-page":"423","volume-title":"Proceedings of the 41st Annual Meeting on Association for Computational Linguistics. Volume 1","author":"D Klein","year":"2003","unstructured":"Klein D, Manning CD: Accurate unlexicalized parsing. Proceedings of the 41st Annual Meeting on Association for Computational Linguistics. Volume 1. 2003, Sapporo, Japan: Association for Computational Linguistics, 423-430."},{"issue":"1","key":"6285_CR25","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"},{"key":"6285_CR26","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511809071","volume-title":"Introduction to information retrieval (vol. 1). Cambridge: Cambridge University Press;","author":"CD Manning","year":"2008","unstructured":"Manning CD, Raghavan P, Schutze H: Introduction to information retrieval (vol. 1). Cambridge: Cambridge University Press;. 2008"},{"key":"6285_CR27","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1038\/msb.2009.98","volume":"6","author":"M Kuhn","year":"201","unstructured":"Kuhn M, Campillos M, Letunic I, Jensen LJ, Bork P: A side effect resource to capture phenotypic effects of drugs. Mol Syst Biol. 201, 6: 343-doi: 10.1038\/msb.2009.98.,","journal-title":"Mol Syst Biol"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/1471-2105-15-17.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/1471-2105-15-17\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/1471-2105-15-17.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,6]],"date-time":"2019-08-06T11:43:42Z","timestamp":1565091822000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/1471-2105-15-17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,1,15]]},"references-count":27,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2014,12]]}},"alternative-id":["6285"],"URL":"https:\/\/doi.org\/10.1186\/1471-2105-15-17","relation":{},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,1,15]]},"article-number":"17"}}