{"id":"https://openalex.org/W4388674344","doi":"https://doi.org/10.1109/bhi58575.2023.10313411","title":"Towards Accurate and Clinically Meaningful Summarization of Electronic Health Record Notes: A Guided Approach","display_name":"Towards Accurate and Clinically Meaningful Summarization of Electronic Health Record Notes: A Guided Approach","publication_year":2023,"publication_date":"2023-10-15","ids":{"openalex":"https://openalex.org/W4388674344","doi":"https://doi.org/10.1109/bhi58575.2023.10313411"},"language":"en","primary_location":{"id":"doi:10.1109/bhi58575.2023.10313411","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bhi58575.2023.10313411","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI)","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/A5033977699","display_name":"Zhimeng Luo","orcid":"https://orcid.org/0000-0002-7573-4530"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhimeng Luo","raw_affiliation_strings":["University of Pittsburgh,School of Computing and Information,Pittsburgh,USA","School of Computing and Information, University of Pittsburgh, Pittsburgh, USA"],"affiliations":[{"raw_affiliation_string":"University of Pittsburgh,School of Computing and Information,Pittsburgh,USA","institution_ids":["https://openalex.org/I170201317"]},{"raw_affiliation_string":"School of Computing and Information, University of Pittsburgh, Pittsburgh, USA","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026482925","display_name":"Yuelyu Ji","orcid":"https://orcid.org/0000-0001-6389-5823"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuelyu Ji","raw_affiliation_strings":["University of Pittsburgh,School of Computing and Information,Pittsburgh,USA","School of Computing and Information, University of Pittsburgh, Pittsburgh, USA"],"affiliations":[{"raw_affiliation_string":"University of Pittsburgh,School of Computing and Information,Pittsburgh,USA","institution_ids":["https://openalex.org/I170201317"]},{"raw_affiliation_string":"School of Computing and Information, University of Pittsburgh, Pittsburgh, USA","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015694470","display_name":"Abhibha Gupta","orcid":null},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abhibha Gupta","raw_affiliation_strings":["University of Pittsburgh,School of Computing and Information,Pittsburgh,USA","School of Computing and Information, University of Pittsburgh, Pittsburgh, USA"],"affiliations":[{"raw_affiliation_string":"University of Pittsburgh,School of Computing and Information,Pittsburgh,USA","institution_ids":["https://openalex.org/I170201317"]},{"raw_affiliation_string":"School of Computing and Information, University of Pittsburgh, Pittsburgh, USA","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028914229","display_name":"Zhuochun Li","orcid":null},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhuochun Li","raw_affiliation_strings":["University of Pittsburgh,School of Computing and Information,Pittsburgh,USA","School of Computing and Information, University of Pittsburgh, Pittsburgh, USA"],"affiliations":[{"raw_affiliation_string":"University of Pittsburgh,School of Computing and Information,Pittsburgh,USA","institution_ids":["https://openalex.org/I170201317"]},{"raw_affiliation_string":"School of Computing and Information, University of Pittsburgh, Pittsburgh, USA","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110695143","display_name":"Adam Frisch","orcid":null},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Adam Frisch","raw_affiliation_strings":["University of Pittsburgh,Department of Emergency Medicine,Pittsburgh,USA","Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, USA"],"affiliations":[{"raw_affiliation_string":"University of Pittsburgh,Department of Emergency Medicine,Pittsburgh,USA","institution_ids":["https://openalex.org/I170201317"]},{"raw_affiliation_string":"Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, USA","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038618246","display_name":"Daqing He","orcid":null},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daqing He","raw_affiliation_strings":["University of Pittsburgh,School of Computing and Information,Pittsburgh,USA","School of Computing and Information, University of Pittsburgh, Pittsburgh, USA"],"affiliations":[{"raw_affiliation_string":"University of Pittsburgh,School of Computing and Information,Pittsburgh,USA","institution_ids":["https://openalex.org/I170201317"]},{"raw_affiliation_string":"School of Computing and Information, University of Pittsburgh, Pittsburgh, USA","institution_ids":["https://openalex.org/I170201317"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5033977699"],"corresponding_institution_ids":["https://openalex.org/I170201317"],"apc_list":null,"apc_paid":null,"fwci":1.049,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.81760025,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9986000061035156,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9973000288009644,"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/automatic-summarization","display_name":"Automatic summarization","score":0.9254260063171387},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8022369146347046},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5205144286155701},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5019998550415039},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.46624746918678284},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.4514656066894531},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4220591187477112},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4127740263938904},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.34166228771209717},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3360769748687744}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.9254260063171387},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8022369146347046},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5205144286155701},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5019998550415039},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.46624746918678284},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.4514656066894531},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4220591187477112},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4127740263938904},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.34166228771209717},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3360769748687744},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bhi58575.2023.10313411","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bhi58575.2023.10313411","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7599999904632568,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W378747138","https://openalex.org/W2130942839","https://openalex.org/W2159583324","https://openalex.org/W2183341477","https://openalex.org/W2396881363","https://openalex.org/W2750779823","https://openalex.org/W2799364415","https://openalex.org/W2803930360","https://openalex.org/W2963716420","https://openalex.org/W2986128626","https://openalex.org/W3012542822","https://openalex.org/W3034999214","https://openalex.org/W3111372071","https://openalex.org/W3159493748","https://openalex.org/W3196696529","https://openalex.org/W4205088978","https://openalex.org/W4238846128","https://openalex.org/W4285116827","https://openalex.org/W4311829616","https://openalex.org/W4385573581","https://openalex.org/W6612948155","https://openalex.org/W6679436768","https://openalex.org/W6682631176","https://openalex.org/W6775500230","https://openalex.org/W6776859438","https://openalex.org/W6784101632","https://openalex.org/W6796636777","https://openalex.org/W6796727985","https://openalex.org/W6809909653"],"related_works":["https://openalex.org/W2366403280","https://openalex.org/W1495108544","https://openalex.org/W2091301346","https://openalex.org/W3148229873","https://openalex.org/W2150160875","https://openalex.org/W4242223894","https://openalex.org/W1517524280","https://openalex.org/W4323520239","https://openalex.org/W4389760904","https://openalex.org/W2369835347"],"abstract_inverted_index":{"Clinicians":[0],"are":[1,16,59],"often":[2],"under":[3],"time":[4],"pressure":[5],"when":[6,199],"they":[7],"review":[8],"patients\u2019":[9,25],"electronic":[10],"health":[11],"records":[12],"(EHR),":[13],"therefore,":[14],"there":[15],"great":[17],"benefits":[18],"to":[19,49,70,193,215,219],"providing":[20],"clinicians":[21,58],"high-quality":[22],"summarizations":[23],"of":[24,139,158,182,187,223,230],"EHR.":[26],"However,":[27],"existing":[28],"summarization":[29,77,222],"algorithms":[30],"fall":[31],"short":[32],"in":[33,161],"certain":[34],"key":[35],"aspects,":[36],"such":[37],"as":[38],"focusing":[39],"on":[40,117,203],"pertinent":[41],"information":[42],"that":[43,53,126],"is":[44,207],"clinically":[45,165],"significant,":[46],"and":[47,97,104,144,164,190,210,234],"adhering":[48],"a":[50,67,75,82,87,91,105,118],"structured":[51,83],"template":[52,84],"aligns":[54],"with":[55,86,172,226],"the":[56,110,137,147,156,159,174,178,185,196,200,204,216,221,227],"formats":[57],"accustomed":[60],"to.":[61],"In":[62],"this":[63],"paper,":[64],"we":[65],"present":[66],"novel":[68],"approach":[69],"summarize":[71],"EHR":[72,121,224],"notes":[73],"using":[74],"guided":[76],"model.":[78],"Our":[79],"model":[80,96,100,116,171],"integrates":[81],"developed":[85],"clinical":[88,205],"domain":[89,198,206],"expert,":[90],"Named":[92],"Entity":[93],"Recognition":[94],"(NER)":[95],"sentence":[98],"classification":[99],"for":[101,108],"guidance":[102,135,145,175,192],"extraction,":[103],"fact-checking":[106],"metric":[107],"evaluating":[109],"generated":[111],"summaries.":[112,167],"We":[113],"trained":[114],"our":[115,127],"large":[119],"de-identified":[120],"dataset.":[122],"The":[123,168],"results":[124],"demonstrate":[125],"guidance,":[128],"which":[129],"includes":[130],"Chief":[131],"Complaint":[132],"(CC),":[133],"NER,":[134],"from":[136,146,195],"History":[138],"Present":[140],"Illness":[141],"(HPI)":[142],"section,":[143,152],"Medical":[148],"Decision":[149],"Making":[150],"(MDM)":[151],"can":[153],"significantly":[154],"improve":[155],"performance":[157],"models":[160,194],"generating":[162],"accurate":[163],"meaningful":[166],"Gsum":[169],"(CNN)":[170],"all":[173],"aforementioned":[176],"achieved":[177],"highest":[179],"F1":[180],"score":[181],"46.4,":[183],"demonstrating":[184],"effectiveness":[186],"introducing":[188],"precise":[189],"informative":[191],"general":[197],"training":[201],"data":[202],"prohibitively":[208],"sensitive":[209],"expensive.":[211],"This":[212],"work":[213],"contributes":[214],"ongoing":[217],"efforts":[218],"automate":[220],"notes,":[225],"ultimate":[228],"goal":[229],"improving":[231],"healthcare":[232],"delivery":[233],"patient":[235],"outcomes.":[236]},"counts_by_year":[{"year":2024,"cited_by_count":6}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}
