{"id":"https://openalex.org/W7126056858","doi":"https://doi.org/10.1109/bibm66473.2025.11355985","title":"Integrating Clinical Knowledge into Radiology Report Generation to Enhance Diagnosis","display_name":"Integrating Clinical Knowledge into Radiology Report Generation to Enhance Diagnosis","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126056858","doi":"https://doi.org/10.1109/bibm66473.2025.11355985"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11355985","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11355985","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5124253307","display_name":"Zhenqian Cao","orcid":null},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenqian Cao","raw_affiliation_strings":["School of Future Technology, Shanghai University,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Future Technology, Shanghai University,Shanghai,China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124184021","display_name":"Xiaodong Yue","orcid":null},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaodong Yue","raw_affiliation_strings":["School of Future Technology, Shanghai University,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Future Technology, Shanghai University,Shanghai,China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124173958","display_name":"Yufei Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yufei Chen","raw_affiliation_strings":["College of Electronic and Information Engineering, Tongji University,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronic and Information Engineering, Tongji University,Shanghai,China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091903711","display_name":"Zhikang Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhikang Xu","raw_affiliation_strings":["Institute of Intelligent Information Processing, Shanxi University,Taiyuan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Intelligent Information Processing, Shanxi University,Taiyuan,China","institution_ids":["https://openalex.org/I181877577"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhipeng Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhipeng Wei","raw_affiliation_strings":["School of Computer Engineering and Science, Shanghai University,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University,Shanghai,China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051757118","display_name":"Zihao Li","orcid":"https://orcid.org/0000-0003-4830-8621"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zihao Li","raw_affiliation_strings":["School of Computer Engineering and Science, Shanghai University,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University,Shanghai,China","institution_ids":["https://openalex.org/I141962983"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5597","last_page":"5602"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.38519999384880066,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.38519999384880066,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10028","display_name":"Topic Modeling","score":0.16369999945163727,"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/T11894","display_name":"Radiology practices and education","score":0.14810000360012054,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.5429999828338623},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.4945000112056732},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4207000136375427},{"id":"https://openalex.org/keywords/clinical-practice","display_name":"Clinical Practice","score":0.4138999879360199},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.3732999861240387},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.3716000020503998},{"id":"https://openalex.org/keywords/clinical-diagnosis","display_name":"Clinical diagnosis","score":0.3303999900817871}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6013000011444092},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.5429999828338623},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.4945000112056732},{"id":"https://openalex.org/C19527891","wikidata":"https://www.wikidata.org/wiki/Q1120908","display_name":"Medical physics","level":1,"score":0.46700000762939453},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4207000136375427},{"id":"https://openalex.org/C2779974597","wikidata":"https://www.wikidata.org/wiki/Q28448986","display_name":"Clinical Practice","level":2,"score":0.4138999879360199},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4059000015258789},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.3732999861240387},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.3716000020503998},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.33500000834465027},{"id":"https://openalex.org/C2983449737","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Clinical diagnosis","level":2,"score":0.3303999900817871},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3206999897956848},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31189998984336853},{"id":"https://openalex.org/C534262118","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Medical diagnosis","level":2,"score":0.303600013256073},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3034000098705292},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.2703999876976013},{"id":"https://openalex.org/C2985722590","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medical knowledge","level":2,"score":0.26600000262260437},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.26269999146461487},{"id":"https://openalex.org/C63363279","wikidata":"https://www.wikidata.org/wiki/Q5133848","display_name":"Clinical significance","level":2,"score":0.25949999690055847},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2590999901294708},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2581000030040741}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11355985","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11355985","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7270339727401733,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G8385298718","display_name":null,"funder_award_id":"62476165,62472315,62406182","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1600834507","https://openalex.org/W2101105183","https://openalex.org/W2152772232","https://openalex.org/W2997704374","https://openalex.org/W3103694015","https://openalex.org/W3104609094","https://openalex.org/W3130502265","https://openalex.org/W3181252431","https://openalex.org/W4231122779","https://openalex.org/W4281729070","https://openalex.org/W4283821415","https://openalex.org/W4360604432","https://openalex.org/W4386065580","https://openalex.org/W4386076127","https://openalex.org/W4386076360","https://openalex.org/W4386076536","https://openalex.org/W4389665166","https://openalex.org/W4393159390"],"related_works":[],"abstract_inverted_index":{"The":[0],"automatic":[1],"generation":[2,130],"of":[3,18,45,49],"medical":[4,119],"imaging":[5],"reports":[6,34],"has":[7],"significant":[8],"research":[9],"value,":[10],"as":[11],"it":[12],"can":[13],"alleviate":[14],"the":[15,46,113,129],"heavy":[16],"workload":[17],"radiologists":[19],"and":[20,74,126,137,156],"reduce":[21],"diagnostic":[22,91],"biases.":[23],"Existing":[24],"methods":[25,148],"mostly":[26],"focus":[27],"on":[28],"text":[29],"fluency,":[30],"ensuring":[31],"that":[32,66,143],"generated":[33],"align":[35],"with":[36,109],"ground":[37],"truth.":[38],"However,":[39],"this":[40,59],"leads":[41],"to":[42,70,115],"a":[43,63],"neglect":[44],"effective":[47],"integration":[48],"clinical":[50,55,68,72,95,99,110,135,154],"knowledge,":[51,96,111],"resulting":[52],"in":[53],"poor":[54],"accuracy.":[56,100],"To":[57],"address":[58],"limitation,":[60],"we":[61,78],"propose":[62],"novel":[64],"framework":[65,145],"incorporates":[67],"knowledge":[69],"improve":[71],"accuracy":[73,155],"report":[75],"generation.":[76],"Specifically,":[77],"introduce":[79],"Multi-Expert":[80],"Knowledge":[81],"Enhanced":[82],"Prompt":[83],"Learning":[84,104],"(KEP),":[85],"which":[86],"generates":[87],"more":[88,117],"reliable":[89],"disease":[90],"prompts":[92,125],"by":[93],"integrating":[94,122],"thereby":[97],"enhancing":[98],"Additionally,":[101],"Knowledge-Enhanced":[102],"Feature":[103],"(KEF)":[105],"enhances":[106],"image":[107],"features":[108,127],"enabling":[112],"decoder":[114],"incorporate":[116],"comprehensive":[118],"information.":[120],"By":[121],"these":[123],"knowledge-driven":[124],"into":[128],"model,":[131],"our":[132,144],"approach":[133],"ensures":[134],"relevance":[136],"textual":[138],"coherence.":[139],"Experimental":[140],"results":[141],"demonstrate":[142],"outperforms":[146],"previous":[147],"across":[149],"multiple":[150],"benchmarks,":[151],"achieving":[152],"superior":[153],"linguistic":[157],"fidelity.":[158]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-01-30T00:00:00"}
