{"id":"https://openalex.org/W2911525976","doi":"https://doi.org/10.1109/bibm.2018.8621195","title":"Boundary Detection by Determining the Difference of Classification Probabilities of Sequences: Topic Segmentation of Clinical Notes","display_name":"Boundary Detection by Determining the Difference of Classification Probabilities of Sequences: Topic Segmentation of Clinical Notes","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2911525976","doi":"https://doi.org/10.1109/bibm.2018.8621195","mag":"2911525976"},"language":"en","primary_location":{"id":"doi:10.1109/bibm.2018.8621195","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm.2018.8621195","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5086385122","display_name":"Ruan Wei","orcid":"https://orcid.org/0009-0007-0046-9254"},"institutions":[{"id":"https://openalex.org/I153718931","display_name":"University of Ottawa","ror":"https://ror.org/03c4mmv16","country_code":"CA","type":"education","lineage":["https://openalex.org/I153718931"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Wei Ruan","raw_affiliation_strings":["School of Electrical Engineering and Computer Science (EECS), University of Ottawa, Ottawa, Canada"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science (EECS), University of Ottawa, Ottawa, Canada","institution_ids":["https://openalex.org/I153718931"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063382504","display_name":"Won\u2010Sook Lee","orcid":"https://orcid.org/0000-0003-3024-3081"},"institutions":[{"id":"https://openalex.org/I153718931","display_name":"University of Ottawa","ror":"https://ror.org/03c4mmv16","country_code":"CA","type":"education","lineage":["https://openalex.org/I153718931"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Won-sook Lee","raw_affiliation_strings":["School of Electrical Engineering and Computer Science (EECS), University of Ottawa, Ottawa, Canada"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science (EECS), University of Ottawa, Ottawa, Canada","institution_ids":["https://openalex.org/I153718931"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5086385122"],"corresponding_institution_ids":["https://openalex.org/I153718931"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.13255221,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"23 1","issue":null,"first_page":"747","last_page":"750"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9997000098228455,"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/T10028","display_name":"Topic Modeling","score":0.9983999729156494,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.996399998664856,"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/support-vector-machine","display_name":"Support vector machine","score":0.66314697265625},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6340407133102417},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5843378901481628},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.5667286515235901},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5176599621772766},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.5075215101242065},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4240868091583252},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.4208899140357971},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.41597509384155273},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.405937135219574},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3409183621406555},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2996487021446228},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.1117391288280487}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.66314697265625},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6340407133102417},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5843378901481628},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5667286515235901},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5176599621772766},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.5075215101242065},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4240868091583252},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.4208899140357971},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.41597509384155273},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.405937135219574},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3409183621406555},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2996487021446228},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.1117391288280487},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm.2018.8621195","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm.2018.8621195","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1456619997","https://openalex.org/W1557074680","https://openalex.org/W1828401780","https://openalex.org/W1862888253","https://openalex.org/W1975685775","https://openalex.org/W2048151729","https://openalex.org/W2066733218","https://openalex.org/W2154593091","https://openalex.org/W2159083595","https://openalex.org/W2159583324","https://openalex.org/W2565495132","https://openalex.org/W2886305294","https://openalex.org/W6628391794","https://openalex.org/W6638575021","https://openalex.org/W6638891705","https://openalex.org/W6682767229","https://openalex.org/W6731456550"],"related_works":["https://openalex.org/W2090763504","https://openalex.org/W148178222","https://openalex.org/W2394466068","https://openalex.org/W1987683558","https://openalex.org/W2104657898","https://openalex.org/W1948992892","https://openalex.org/W1886884218","https://openalex.org/W1910826599","https://openalex.org/W2012353789","https://openalex.org/W2417174640"],"abstract_inverted_index":{"Topic":[0,86],"segmentation":[1,31],"of":[2,20,29,42,45,80,105],"clinical":[3,33,51],"notes":[4,34,52],"is":[5],"a":[6,27,77,94,110,147],"significant":[7],"issue":[8],"in":[9,98],"the":[10,18,40,103,106,115,134,141],"information":[11],"retrieval":[12],"domain":[13],"that":[14,89,175],"could":[15],"effectively":[16],"help":[17],"process":[19],"diagnosis.":[21],"In":[22],"this":[23],"study,":[24],"we":[25,56],"propose":[26],"methodology":[28],"topic":[30,144],"to":[32,84,109,174],"with":[35,76,93],"boundary":[36],"detection":[37],"by":[38,139],"determining":[39],"difference":[41],"classification":[43],"probabilities":[44],"sequences.":[46],"With":[47],"1127":[48],"text":[49],"plain":[50],"collected":[53],"from":[54],"I2B2":[55],"experiment":[57],"on":[58,168,177],"5":[59],"topics:":[60],"medications,":[61],"history,":[62],"hospital":[63],"course,":[64],"laboratories":[65],"and":[66,72,153,187],"physical":[67],"exams.":[68],"The":[69],"Naive":[70,169],"Bayes":[71,170],"Linear":[73],"SVM":[74,178],"models":[75],"selected":[78],"feature":[79],"BOW":[81],"are":[82,160],"employed":[83],"train":[85],"Score":[87,158,193],"Predictors":[88],"assign":[90],"each":[91,100],"sequence":[92,107],"5-dimensional":[95],"vector":[96,116],"vi":[97],"which":[99],"element":[101],"represents":[102],"probability":[104],"belonging":[108],"corresponding":[111],"class.":[112],"By":[113],"analyzing":[114],"\u03c1":[117],"=":[118],"[v":[119],"<sub":[120,125,130,155,190],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[121,126,131,156,191],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[122,157,192],",":[123,128],"v":[124],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sub>":[127],"......v":[129],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">i</sub>":[132],"],":[133],"boundaries":[135],"would":[136],"be":[137],"detected":[138],"finding":[140],"locations":[142],"where":[143],"scores":[145],"have":[146],"rapid":[148],"change.":[149],"Famous":[150],"Windiff,":[151,183],"Pk":[152,186],"F":[154,189],"metrics":[159],"used":[161],"for":[162,182,185],"evaluating":[163],"our":[164],"system.":[165],"Segmenter":[166],"based":[167,176],"shows":[171],"superior":[172],"performance":[173],"model":[179],"having":[180],"0.1468":[181],"0.1221":[184],"averaged":[188],"over":[194],"0.90.":[195]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}