{"id":"https://openalex.org/W2977820536","doi":"https://doi.org/10.18653/v1/d19-6218","title":"Writing habits and telltale neighbors: analyzing clinical concept usage patterns with sublanguage embeddings","display_name":"Writing habits and telltale neighbors: analyzing clinical concept usage patterns with sublanguage embeddings","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2977820536","doi":"https://doi.org/10.18653/v1/d19-6218","mag":"2977820536"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d19-6218","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d19-6218","pdf_url":"https://www.aclweb.org/anthology/D19-6218.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Tenth International Workshop on Health Text Mining and Information Analysis (LOUHI 2019)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/D19-6218.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039754917","display_name":"Denis Newman-Griffis","orcid":"https://orcid.org/0000-0002-0473-4226"},"institutions":[{"id":"https://openalex.org/I1299303238","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88","country_code":"US","type":"government","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238"]},{"id":"https://openalex.org/I4210155647","display_name":"National Institutes of Health Clinical Center","ror":"https://ror.org/04vfsmv21","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I4210155647"]},{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Denis Newman-Griffis","raw_affiliation_strings":["Dept of Computer Science and Engineering, The Ohio State University, Columbus, OH","Rehabilitation Medicine Dept, Clinical Center, National Institutes of Health, Bethesda, MD","National Institutes of Health, Bethesda, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept of Computer Science and Engineering, The Ohio State University, Columbus, OH","institution_ids":["https://openalex.org/I52357470"]},{"raw_affiliation_string":"Rehabilitation Medicine Dept, Clinical Center, National Institutes of Health, Bethesda, MD","institution_ids":["https://openalex.org/I4210155647"]},{"raw_affiliation_string":"National Institutes of Health, Bethesda, United States","institution_ids":["https://openalex.org/I1299303238"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056667180","display_name":"Eric Fosler\u2010Lussier","orcid":"https://orcid.org/0000-0001-8004-5169"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eric Fosler-Lussier","raw_affiliation_strings":["Dept of Computer Science and Engineering, The Ohio State University, Columbus, OH","The Ohio State University, Columbus, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept of Computer Science and Engineering, The Ohio State University, Columbus, OH","institution_ids":["https://openalex.org/I52357470"]},{"raw_affiliation_string":"The Ohio State University, Columbus, United States","institution_ids":["https://openalex.org/I52357470"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"146","last_page":"156"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/sublanguage","display_name":"Sublanguage","score":0.8564987182617188},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7398830056190491},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4907709062099457},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4801868200302124},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.45913058519363403},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.41222718358039856},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38855302333831787}],"concepts":[{"id":"https://openalex.org/C2776411971","wikidata":"https://www.wikidata.org/wiki/Q17141398","display_name":"Sublanguage","level":2,"score":0.8564987182617188},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7398830056190491},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4907709062099457},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4801868200302124},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.45913058519363403},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.41222718358039856},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38855302333831787},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.18653/v1/d19-6218","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d19-6218","pdf_url":"https://www.aclweb.org/anthology/D19-6218.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Tenth International Workshop on Health Text Mining and Information Analysis (LOUHI 2019)","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.whiterose.ac.uk:196488","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306400854","display_name":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2800616092","host_organization_name":"White Rose University Consortium","host_organization_lineage":["https://openalex.org/I2800616092"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Proceedings Paper"},{"id":"pmh:oai:arXiv.org:1910.00192","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1910.00192","pdf_url":"https://arxiv.org/pdf/1910.00192","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:2977820536","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1910.00192","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1910.00192","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1910.00192","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.18653/v1/d19-6218","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d19-6218","pdf_url":"https://www.aclweb.org/anthology/D19-6218.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Tenth International Workshop on Health Text Mining and Information Analysis (LOUHI 2019)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.8700000047683716,"display_name":"Quality Education"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320308309","display_name":"U.S. Social Security Administration","ror":"https://ror.org/04b7xxn32"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2977820536.pdf","grobid_xml":"https://content.openalex.org/works/W2977820536.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W1492103924","https://openalex.org/W2087834911","https://openalex.org/W2093157872","https://openalex.org/W2099307202","https://openalex.org/W2122402213","https://openalex.org/W2146089916","https://openalex.org/W2159583324","https://openalex.org/W2284851926","https://openalex.org/W2396881363","https://openalex.org/W2401839734","https://openalex.org/W2407557870","https://openalex.org/W2516535623","https://openalex.org/W2560448473","https://openalex.org/W2574229915","https://openalex.org/W2769358515","https://openalex.org/W2882319491","https://openalex.org/W2917968119","https://openalex.org/W2949845972","https://openalex.org/W2963654293","https://openalex.org/W2963780471","https://openalex.org/W2970195734"],"related_works":["https://openalex.org/W2986924095","https://openalex.org/W2287180041","https://openalex.org/W3138340848","https://openalex.org/W2085761430","https://openalex.org/W2737033911","https://openalex.org/W2990464738","https://openalex.org/W571094121","https://openalex.org/W3118453445","https://openalex.org/W2943564362","https://openalex.org/W3103971440","https://openalex.org/W3083505326","https://openalex.org/W1865748020","https://openalex.org/W3185824387","https://openalex.org/W2790074249","https://openalex.org/W2094761690","https://openalex.org/W2252071100","https://openalex.org/W3209240709","https://openalex.org/W2436312382","https://openalex.org/W2523342174","https://openalex.org/W2901020213"],"abstract_inverted_index":{"Natural":[0],"language":[1],"processing":[2],"techniques":[3],"are":[4,75],"being":[5],"applied":[6],"to":[7,47,77,110],"increasingly":[8],"diverse":[9],"types":[10,64],"of":[11,21,25,38,62,114],"electronic":[12],"health":[13],"records,":[14],"and":[15,65,105],"can":[16],"benefit":[17],"from":[18],"in-depth":[19],"understanding":[20],"the":[22,35,52,67,92],"distinguishing":[23],"characteristics":[24,113],"medical":[26],"document":[27,43,116],"types.":[28],"We":[29],"present":[30],"a":[31],"method":[32],"for":[33,85],"characterizing":[34],"usage":[36,82,104],"patterns":[37],"clinical":[39,60,115],"concepts":[40],"among":[41],"different":[42,63],"types,":[44],"in":[45,69,80,87,102],"order":[46],"capture":[48],"semantic":[49,112],"differences":[50,68,101],"beyond":[51],"lexical":[53],"level.":[54],"By":[55],"training":[56],"concept":[57,81,103],"embeddings":[58],"on":[59,91],"documents":[61],"measuring":[66],"their":[70],"nearest":[71],"neighborhood":[72],"structures,":[73],"we":[74],"able":[76],"measure":[78],"divergences":[79],"while":[83],"correcting":[84],"noise":[86],"embedding":[88],"learning.":[89],"Experiments":[90],"MIMIC-III":[93],"corpus":[94],"demonstrate":[95],"that":[96],"our":[97],"approach":[98],"captures":[99],"clinically-relevant":[100],"provides":[106],"an":[107],"intuitive":[108],"way":[109],"explore":[111],"collections.":[117]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
