{"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/enhancing-drug-drug-interaction-extraction","title":"Enhancing Drug-Drug Interaction Extraction from Texts by Molecular Structure Information","arxiv_id":"1805.05593","date":"2018-05-15","proceeding":"ACL 2018 7","authors":["Masaki Asada","Makoto Miwa","Yutaka Sasaki"],"abstract":"We propose a novel neural method to extract drug-drug interactions (DDIs)\nfrom texts using external drug molecular structure information. We encode\ntextual drug pairs with convolutional neural networks and their molecular pairs\nwith graph convolutional networks (GCNs), and then we concatenate the outputs\nof these two networks. In the experiments, we show that GCNs can predict DDIs\nfrom the molecular structures of drugs in high accuracy and the molecular\ninformation can enhance text-based DDI extraction by 2.39 percent points in the\nF-score on the DDIExtraction 2013 shared task data set.","url_abs":"http://arxiv.org/abs/1805.05593v1","url_pdf":"http://arxiv.org/pdf/1805.05593v1.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":[],"tasks":[{"task_slug":"drug-drug-interaction-extraction","task_name":"Drug–drug Interaction Extraction"}],"methods":[{"method_slug":"graph-convolutional-networks","method_name":"Graph Convolutional Networks"}],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/drug-drug-interaction-extraction-on-ddi","task":"Drug–drug Interaction Extraction","dataset":"DDI extraction 2013 corpus","model":"MOL+CNN","rank_in_archive_order":6,"of":10,"metrics":{"F1":"0.7255","Micro F1":"72.55"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1805.05593","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}