{"id":"https://openalex.org/W2922170191","doi":"https://doi.org/10.1109/icosc.2019.8665548","title":"Distributional Semantics of Clinical Words","display_name":"Distributional Semantics of Clinical Words","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2922170191","doi":"https://doi.org/10.1109/icosc.2019.8665548","mag":"2922170191"},"language":"en","primary_location":{"id":"doi:10.1109/icosc.2019.8665548","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icosc.2019.8665548","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 13th International Conference on Semantic Computing (ICSC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103861930","display_name":"Vamsi Krishna","orcid":null},"institutions":[{"id":"https://openalex.org/I4210133649","display_name":"Philips (India)","ror":"https://ror.org/0435vfk93","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210122849","https://openalex.org/I4210133649"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Vamsi Krishna","raw_affiliation_strings":["Philips HealthSuite Insights, Philips Healthcare, Bangalore, India"],"affiliations":[{"raw_affiliation_string":"Philips HealthSuite Insights, Philips Healthcare, Bangalore, India","institution_ids":["https://openalex.org/I4210133649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015962480","display_name":"Srikanth Mujjiga","orcid":null},"institutions":[{"id":"https://openalex.org/I4210133649","display_name":"Philips (India)","ror":"https://ror.org/0435vfk93","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210122849","https://openalex.org/I4210133649"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Srikanth Mujjiga","raw_affiliation_strings":["Philips HealthSuite Insights, Philips Healthcare, Bangalore, India"],"affiliations":[{"raw_affiliation_string":"Philips HealthSuite Insights, Philips Healthcare, Bangalore, India","institution_ids":["https://openalex.org/I4210133649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013782044","display_name":"Kalyan Chakravarthil","orcid":null},"institutions":[{"id":"https://openalex.org/I4210133649","display_name":"Philips (India)","ror":"https://ror.org/0435vfk93","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210122849","https://openalex.org/I4210133649"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Kalyan Chakravarthil","raw_affiliation_strings":["Philips HealthSuite Insights, Philips Healthcare, Bangalore, India"],"affiliations":[{"raw_affiliation_string":"Philips HealthSuite Insights, Philips Healthcare, Bangalore, India","institution_ids":["https://openalex.org/I4210133649"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110630278","display_name":"J. Vijayananda","orcid":null},"institutions":[{"id":"https://openalex.org/I4210133649","display_name":"Philips (India)","ror":"https://ror.org/0435vfk93","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210122849","https://openalex.org/I4210133649"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"J. Vijayananda","raw_affiliation_strings":["Philips HealthSuite Insights, Philips Healthcare, Bangalore, India"],"affiliations":[{"raw_affiliation_string":"Philips HealthSuite Insights, Philips Healthcare, Bangalore, India","institution_ids":["https://openalex.org/I4210133649"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103861930"],"corresponding_institution_ids":["https://openalex.org/I4210133649"],"apc_list":null,"apc_paid":null,"fwci":0.28,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.63586452,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"106","last_page":"109"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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":0.9998999834060669,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9976000189781189,"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":0.9976000189781189,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8107190132141113},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7252635955810547},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6620645523071289},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6344641447067261},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6251361966133118},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.5688174366950989},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5437847375869751},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5155565738677979},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4799942672252655},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.47639337182044983},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4125209152698517},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.23834776878356934},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07696405053138733}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8107190132141113},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7252635955810547},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6620645523071289},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6344641447067261},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6251361966133118},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.5688174366950989},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5437847375869751},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5155565738677979},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4799942672252655},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.47639337182044983},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4125209152698517},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.23834776878356934},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07696405053138733},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icosc.2019.8665548","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icosc.2019.8665548","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 13th International Conference on Semantic Computing (ICSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.44999998807907104,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1550258693","https://openalex.org/W1614298861","https://openalex.org/W1832693441","https://openalex.org/W2005430761","https://openalex.org/W2055981215","https://openalex.org/W2095444228","https://openalex.org/W2153579005","https://openalex.org/W2159583324","https://openalex.org/W2184761667","https://openalex.org/W2250539671","https://openalex.org/W2250879510","https://openalex.org/W2294865516","https://openalex.org/W2396881363","https://openalex.org/W2471579714","https://openalex.org/W2585785990","https://openalex.org/W2604418969","https://openalex.org/W2604599254","https://openalex.org/W4294170691","https://openalex.org/W6632766574","https://openalex.org/W6636510571","https://openalex.org/W6682691769","https://openalex.org/W6720402905","https://openalex.org/W6733009957","https://openalex.org/W6735637513"],"related_works":["https://openalex.org/W3201126466","https://openalex.org/W4282827391","https://openalex.org/W4386828785","https://openalex.org/W3165580226","https://openalex.org/W3093943447","https://openalex.org/W3200224724","https://openalex.org/W2440023763","https://openalex.org/W2962474440","https://openalex.org/W4390871823","https://openalex.org/W4320719010"],"abstract_inverted_index":{"Word":[0,27],"embeddings":[1,16,28,46,54,63,119,128,130],"are":[2,29,64,134,152],"the":[3,7,18,56,89,126,158],"distributed":[4],"representation":[5],"of":[6,20,42,53],"words":[8],"in":[9,14,23,44,48,110,157,165],"numerical":[10],"form.":[11],"Recent":[12],"research":[13,43],"word":[15,45,118,123],"shows":[17],"importance":[19],"using":[21],"them":[22],"deep":[24,37,58],"learning":[25,38,59,84],"algorithms.":[26],"commonly":[30],"leveraged":[31],"as":[32],"feature":[33],"inputs":[34],"to":[35,55,87,98,154],"many":[36],"models.":[39],"A":[40],"lot":[41],"helped":[47],"various":[49],"open":[50],"source":[51],"releases":[52],"larger":[57],"community.":[60],"However,":[61],"these":[62],"trained":[65],"on":[66,148],"generic":[67],"corpus":[68],"which":[69],"limits":[70],"their":[71],"use":[72,146],"for":[73,93,107,136],"domain":[74],"specific":[75],"tasks.":[76,169],"In":[77,96],"our":[78,111,117,132],"paper,":[79],"we":[80,101],"propose":[81],"a":[82,138],"transfer":[83],"based":[85],"approach":[86,133],"train":[88],"skip":[90],"gram":[91],"model":[92],"medical":[94],"terms.":[95],"addition":[97],"pre-trained":[99,122,127],"embeddings,":[100],"also":[102,161],"added":[103],"customized":[104],"clinical":[105],"knowledge":[106],"each":[108],"term":[109],"training":[112,137],"data.":[113],"We":[114,151],"have":[115],"compared":[116],"with":[120],"Google":[121],"embeddings.":[124],"Both":[125],"and":[129,143,160],"from":[131],"used":[135],"Named":[139],"entity":[140],"recognition":[141],"classifier":[142],"follow-up":[144],"detection":[145],"case":[147],"radiology":[149],"reports.":[150],"able":[153],"achieve":[155],"improvement":[156],"Fl-score":[159],"observed":[162],"faster":[163],"convergence":[164],"respective":[166],"NLP":[167],"classification":[168]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
