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In this paper, we propose the use of different features with a statical modeling method called conditional random fields, which is consider an algorithm for effectively solving problems of sequence tagging. Our goal is to determine which feature selection can affect the performance of four subtasks presented in SemEval Task-12: Clinical TempEval 2016. We applied a careful preprocessing, where the proposed method was tested on real clinical records from Task-12: Clinical TempEval 2016. The comparative analyses obtained indicate that our proposal achieves good results compared to the work presented in Task-12: Clinical TempEval 2016 challenges.<\/jats:p>","DOI":"10.3233\/jifs-179014","type":"journal-article","created":{"date-parts":[[2019,4,16]],"date-time":"2019-04-16T17:02:47Z","timestamp":1555434167000},"page":"4633-4643","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["Medical events extraction to analyze clinical records with conditional random fields"],"prefix":"10.1177","volume":"36","author":[{"given":"Carolina","family":"F\u00f3cil-Arias","sequence":"first","affiliation":[{"name":"Centro de Investigaci\u00f3n en Computaci\u00f3n, Instituto Polit\u00e9cnico Nacional, Mexico"}]},{"given":"Grigori","family":"Sidorov","sequence":"additional","affiliation":[{"name":"Centro de Investigaci\u00f3n en Computaci\u00f3n, Instituto Polit\u00e9cnico Nacional, Mexico"}]},{"given":"Alexander","family":"Gelbukh","sequence":"additional","affiliation":[{"name":"Centro de Investigaci\u00f3n en Computaci\u00f3n, Instituto Polit\u00e9cnico Nacional, Mexico"}]}],"member":"179","published-online":{"date-parts":[[2019,4,15]]},"reference":[{"key":"e_1_3_3_2_2","unstructured":"Unified medical language system (umls). https:\/\/www.nlm.nih.gov\/research\/umls\/aboutumls.html."},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2015.09.015"},{"key":"e_1_3_3_4_2","first-page":"1256","article-title":"UtahBMI at SemEval-Task 12: Extracting temporalinformation from clinical text","author":"Abdulrahman K.","year":"2016","unstructured":"AbdulrahmanK., VelupillaiS. and MeystreS., UtahBMI at SemEval-Task 12: Extracting temporalinformation from clinical text, In Proc. of the 10th International Workshop SemanticEvaluation (2016), 1256\u20131262.","journal-title":"Proc. of the 10th International Workshop SemanticEvaluation"},{"key":"e_1_3_3_5_2","first-page":"1274","article-title":"Brundlefly at SemEval-Task 12: Recurrent neural networksvs. joint inference for clinical temporal information extraction","author":"Alan Fries J.","year":"2016","unstructured":"Alan FriesJ., Brundlefly at SemEval-Task 12: Recurrent neural networksvs. joint inference for clinical temporal information extraction, In Proc. of the 10th International Workshop SemanticEvaluation (2016), 1274\u20131279.","journal-title":"Proc. of the 10th International Workshop SemanticEvaluation"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2017.11.012"},{"key":"e_1_3_3_7_2","first-page":"820","article-title":"SemEval-Task 12: Clinical TempEval","author":"Bethard S.","year":"2016","unstructured":"BethardS., GuerganaS., CheW.-T., DerczynskiL., PustejovskyJ. and VerhagenM., SemEval-Task 12: Clinical TempEval, In Proceedings of NAACL-HLT 2016 (2016), 820\u2013830.","journal-title":"Proceedings of NAACL-HLT 2016"},{"key":"e_1_3_3_8_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/S17-2093"},{"key":"e_1_3_3_9_2","volume-title":"Natural Language Processing with Python","author":"Bird S.","year":"2009","unstructured":"BirdS., KleinE., LoperE., (2009). 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