{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/structured-prediction-models-for-rnn-based","title":"Structured prediction models for RNN based sequence labeling in clinical text","arxiv_id":"1608.00612","date":"2016-08-01","proceeding":"EMNLP 2016 11","authors":["Abhyuday Jagannatha","Hong Yu"],"abstract":"Sequence labeling is a widely used method for named entity recognition and\ninformation extraction from unstructured natural language data. In clinical\ndomain one major application of sequence labeling involves extraction of\nmedical entities such as medication, indication, and side-effects from\nElectronic Health Record narratives. Sequence labeling in this domain, presents\nits own set of challenges and objectives. In this work we experimented with\nvarious CRF based structured learning models with Recurrent Neural Networks. We\nextend the previously studied LSTM-CRF models with explicit modeling of\npairwise potentials. We also propose an approximate version of skip-chain CRF\ninference with RNN potentials. We use these methodologies for structured\nprediction in order to improve the exact phrase detection of various medical\nentities.","url_abs":"http://arxiv.org/abs/1608.00612v1","url_pdf":"http://arxiv.org/pdf/1608.00612v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"structured-prediction-models-for-rnn-based","repo_url":"https://github.com/abhyudaynj/LSTM-CRF-models","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"named-entity-recognition-1","task_name":"Named Entity Recognition"},{"task_slug":"named-entity-recognition-ner","task_name":"Named Entity Recognition (NER)"},{"task_slug":"structured-prediction","task_name":"Structured Prediction"},{"task_slug":"named-entity-recognition","task_name":"named-entity-recognition"}],"methods":[{"method_slug":"crf","method_name":"CRF"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1608.00612","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}