{"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/medsts-a-resource-for-clinical-semantic","title":"MedSTS: A Resource for Clinical Semantic Textual Similarity","arxiv_id":"1808.09397","date":"2018-08-28","proceeding":null,"authors":["Yanshan Wang","Naveed Afzal","Sunyang Fu","Li-Wei Wang","Feichen Shen","Majid Rastegar-Mojarad","Hongfang Liu"],"abstract":"The wide adoption of electronic health records (EHRs) has enabled a wide\nrange of applications leveraging EHR data. However, the meaningful use of EHR\ndata largely depends on our ability to efficiently extract and consolidate\ninformation embedded in clinical text where natural language processing (NLP)\ntechniques are essential. Semantic textual similarity (STS) that measures the\nsemantic similarity between text snippets plays a significant role in many NLP\napplications. In the general NLP domain, STS shared tasks have made available a\nhuge collection of text snippet pairs with manual annotations in various\ndomains. In the clinical domain, STS can enable us to detect and eliminate\nredundant information that may lead to a reduction in cognitive burden and an\nimprovement in the clinical decision-making process. This paper elaborates our\nefforts to assemble a resource for STS in the medical domain, MedSTS. It\nconsists of a total of 174,629 sentence pairs gathered from a clinical corpus\nat Mayo Clinic. A subset of MedSTS (MedSTS_ann) containing 1,068 sentence pairs\nwas annotated by two medical experts with semantic similarity scores of 0-5\n(low to high similarity). We further analyzed the medical concepts in the\nMedSTS corpus, and tested four STS systems on the MedSTS_ann corpus. In the\nfuture, we will organize a shared task by releasing the MedSTS_ann corpus to\nmotivate the community to tackle the real world clinical problems.","url_abs":"http://arxiv.org/abs/1808.09397v1","url_pdf":"http://arxiv.org/pdf/1808.09397v1.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":"medsts-a-resource-for-clinical-semantic","repo_url":"https://github.com/ncbi-nlp/BioSentVec","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"NOASSERTION"}},{"paper_slug":"medsts-a-resource-for-clinical-semantic","repo_url":"https://github.com/ncbi-nlp/BioWordVec","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"NOASSERTION"}},{"paper_slug":"medsts-a-resource-for-clinical-semantic","repo_url":"https://github.com/sai4july/custext","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"medsts-a-resource-for-clinical-semantic","repo_url":"https://github.com/xiangyue9607/SanText","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"medsts-a-resource-for-clinical-semantic","repo_url":"https://github.com/yangyucheng000/Paper-4/tree/main/MED_MindSpore","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"mindspore","reach":null}],"tasks":[{"task_slug":"decision-making","task_name":"Decision Making"},{"task_slug":"sts","task_name":"STS"},{"task_slug":"semantic-similarity","task_name":"Semantic Similarity"},{"task_slug":"semantic-textual-similarity","task_name":"Semantic Textual Similarity"},{"task_slug":"sentence","task_name":"Sentence"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1808.09397","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}