{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T15:49:41Z","timestamp":1789141781445,"version":"build-2803163510"},"reference-count":30,"publisher":"JMIR Publications Inc.","issue":"11","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Med Inform"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Medical articles covering adverse drug events (ADEs) are systematically reported by pharmaceutical companies for drug safety information purposes. Although policies governing reporting to regulatory bodies vary among countries and regions, all medical article reporting may be categorized as precision or recall based. Recall-based reporting, which is implemented in Japan, requires the reporting of any possible ADE. Therefore, recall-based reporting can introduce numerous false negatives or substantial amounts of noise, a problem that is difficult to address using limited manual labor.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>Our aim was to develop an automated system that could identify ADE-related medical articles, support recall-based reporting, and alleviate manual labor in Japanese pharmaceutical companies.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Using medical articles as input, our system based on natural language processing applies document-level classification to extract articles containing ADEs (replacing manual labor in the first screening) and sentence-level classification to extract sentences within those articles that imply ADEs (thus supporting experts in the second screening). We used 509 Japanese medical articles annotated by a medical engineer to evaluate the performance of the proposed system.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Document-level classification yielded an F1 of 0.903. Sentence-level classification yielded an F1 of 0.413. These were averages of fivefold cross-validations.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>A simple automated system may alleviate the manual labor involved in screening drug safety\u2013related medical articles in pharmaceutical companies. After improving the accuracy of the sentence-level classification by considering a wider context, we intend to apply this system toward real-world postmarketing surveillance.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/22661","type":"journal-article","created":{"date-parts":[[2020,10,28]],"date-time":"2020-10-28T18:47:46Z","timestamp":1603910866000},"page":"e22661","source":"Crossref","is-referenced-by-count":19,"title":["Identification of Adverse Drug Event\u2013Related Japanese Articles: Natural Language Processing Analysis"],"prefix":"10.2196","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9869-4386","authenticated-orcid":false,"given":"Shogo","family":"Ujiie","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6209-1054","authenticated-orcid":false,"given":"Shuntaro","family":"Yada","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9371-1340","authenticated-orcid":false,"given":"Shoko","family":"Wakamiya","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0201-3609","authenticated-orcid":false,"given":"Eiji","family":"Aramaki","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2020,11,27]]},"reference":[{"key":"ref1","unstructured":"World Health OrganizationInternational Drug Monitoring: The Role of the Hospital (Report of a WHO Meeting)19602020-11-17Geneva, SwitzerlandWorld Health Organizationhttps:\/\/apps.who.int\/iris\/bitstream\/handle\/10665\/40747\/WHO_TRS_425.pdf?sequence=1&isAllowed=y"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1365-2125.2006.02698.x"},{"issue":"11","key":"ref3","doi-asserted-by":"crossref","first-page":"915","DOI":"10.1177\/106002808702101114","volume":"21","author":"Rogers, AS","year":"1987","journal-title":"Drug Intell Clin Pharm"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1046\/j.1365-2125.1998.00713.x"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1093\/jamia\/ocz166"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.2196\/12159"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.2196\/11021"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1186\/2041-1480-3-15"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.2196\/medinform.9170"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.3389\/fphar.2018.00541"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1093\/jamia\/ocu041"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.4103\/picr.PICR_89_17"},{"key":"ref13","unstructured":"Food and Drug AdministrationInvestigational New Drug Safety Reporting Requirements for Human Drug and Biological Products and Safety Reporting Requirements for Bioavailability and Bioequivalence Studies in Humans20102020-11-17Silver Spring, MDFood and Drug Administrationhttps:\/\/www.govinfo.gov\/content\/pkg\/FR-2010-09-29\/pdf\/2010-24296.pdf"},{"key":"ref14","unstructured":"European CommissionCommunication from the Commission \u2013 Detailed Guidance on the Collection, Verification and Presentation of Adverse Event\/Reaction Reports Arising from Clinical Trials on Medicinal Products for Human Use (\u2018CT-3\u2019)20112020-11-17Brussels, BelgiumEuropean Commissionhttps:\/\/eur-lex.europa.eu\/LexUriServ\/LexUriServ.do?uri=OJ:C:2011:172:0001:0013:EN:PDF"},{"key":"ref15","unstructured":"Pharmaceuticals and Medical Devices AgencyReports of Side Effects, Infectious Diseases and Defects Based on the Pharmaceutical and Medical Devices Act (for Medical Personnel) (in Japanese)2020-11-17Tokyo, JapanPharmaceuticals and Medical Devices Agencyhttps:\/\/www.pmda.go.jp\/safety\/reports\/hcp\/pmd-act\/0003.html"},{"key":"ref16","unstructured":"NTTDATA NJK CorporationWinReader PRO v.15.02020-11-17https:\/\/mediadrive.jp\/products\/wrp\/"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1177\/001316446002000104"},{"key":"ref18","first-page":"285","volume":"245","author":"Aramaki, E","year":"2017","journal-title":"Stud Health Technol Inform"},{"key":"ref19","unstructured":"ItoKNagaiHOkahisaTWakamiyaSIwaoTAramakiEJ-MeDic: A Japanese disease name dictionary based on real clinical usage2018Proceedings of the Eleventh International Conference on Language Resources and EvaluationMay 7\u201312, 2018Miyazaki, Japan"},{"key":"ref20","unstructured":"Social Computing Laboratory, Nara Institute of Science and TechnologyHYAKUYAKU dictionary.2020-11-17https:\/\/sociocom.naist.jp\/hyakuyaku-dic-en\/"},{"key":"ref21","unstructured":"AramakiEImaiTMiyoKOheKOrthographic disambiguation incorporating transliterated probability2008Proceedings of the Third International Joint Conference on Natural Language ProcessingJan 7\u201312, 2008Hyderabad, Telangana, India"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00254"},{"issue":"85","key":"ref23","first-page":"2825","volume":"12","author":"Pedregosa, F","year":"2011","journal-title":"J Mach Learn Res"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.imu.2019.100190"},{"key":"ref25","unstructured":"KudoTMeCab: Yet Another Part-of-Speech and Morphological Analyzer2020-11-17https:\/\/taku910.github.io\/mecab\/"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2012.04.008"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-15-64"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2015.08.013"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1186\/1472-6947-15-S4-S1"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/bibm.2014.6999216"}],"container-title":["JMIR Medical Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/medinform.jmir.org\/2020\/11\/e22661","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T17:31:28Z","timestamp":1782840688000},"score":1,"resource":{"primary":{"URL":"http:\/\/medinform.jmir.org\/2020\/11\/e22661\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,27]]},"references-count":30,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2020]]}},"URL":"https:\/\/doi.org\/10.2196\/22661","relation":{"has-preprint":[{"id-type":"doi","id":"10.2196\/preprints.22661","asserted-by":"object"}]},"ISSN":["2291-9694"],"issn-type":[{"value":"2291-9694","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,11,27]]}}}