{"id":"https://openalex.org/W7126047952","doi":"https://doi.org/10.1109/bibm66473.2025.11357158","title":"$\\mathrm{D}^{2}$ KGMed: Dynamic Diagnostic Knowledge Graphs for Medical Diagnosis Prediction","display_name":"$\\mathrm{D}^{2}$ KGMed: Dynamic Diagnostic Knowledge Graphs for Medical Diagnosis Prediction","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126047952","doi":"https://doi.org/10.1109/bibm66473.2025.11357158"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11357158","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11357158","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/A5010618416","display_name":"Jie Zhang","orcid":"https://orcid.org/0000-0002-8899-3996"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Zhang","raw_affiliation_strings":["Fuzhou University,Fuzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fuzhou University,Fuzhou,China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124164826","display_name":"Gaoyang Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gaoyang Zheng","raw_affiliation_strings":["Fuzhou University,Fuzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fuzhou University,Fuzhou,China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103160210","display_name":"Hang Lv","orcid":"https://orcid.org/0009-0007-2566-390X"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hang Lv","raw_affiliation_strings":["Fuzhou University,Fuzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fuzhou University,Fuzhou,China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007704896","display_name":"Linhao Luo","orcid":"https://orcid.org/0000-0003-0027-942X"},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Linhao Luo","raw_affiliation_strings":["Monash University,Melbourne,Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Monash University,Melbourne,Australia","institution_ids":["https://openalex.org/I56590836"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124218796","display_name":"Guofang Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I75059550","display_name":"Zhejiang Gongshang University","ror":"https://ror.org/0569mkk41","country_code":"CN","type":"education","lineage":["https://openalex.org/I75059550"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guofang Ma","raw_affiliation_strings":["Zhejiang Gongshang University,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang Gongshang University,Hangzhou,China","institution_ids":["https://openalex.org/I75059550"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124228734","display_name":"Zhigang Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I129708740","display_name":"Fujian Medical University","ror":"https://ror.org/050s6ns64","country_code":"CN","type":"education","lineage":["https://openalex.org/I129708740"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhigang Lin","raw_affiliation_strings":["Fujian Medical University,Fuzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fujian Medical University,Fuzhou,China","institution_ids":["https://openalex.org/I129708740"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124295284","display_name":"Xiping Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I181418319","display_name":"SKEMA Business School","ror":"https://ror.org/036h8vg94","country_code":"FR","type":"education","lineage":["https://openalex.org/I181418319"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Xiping Chen","raw_affiliation_strings":["SKEMA Business School,Suzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SKEMA Business School,Suzhou,China","institution_ids":["https://openalex.org/I181418319"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5115539570","display_name":"Yanchao Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanchao Tan","raw_affiliation_strings":["Fuzhou University,Fuzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fuzhou University,Fuzhou,China","institution_ids":["https://openalex.org/I80947539"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4458","last_page":"4461"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9527000188827515,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9527000188827515,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.03500000014901161,"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/T10028","display_name":"Topic Modeling","score":0.0034000000450760126,"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/medical-diagnosis","display_name":"Medical diagnosis","score":0.6876000165939331},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5439000129699707},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.40560001134872437},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.37040001153945923},{"id":"https://openalex.org/keywords/structuring","display_name":"Structuring","score":0.3231000006198883},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.31200000643730164}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.741599977016449},{"id":"https://openalex.org/C534262118","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Medical diagnosis","level":2,"score":0.6876000165939331},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5925999879837036},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5595999956130981},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5439000129699707},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4083999991416931},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.40560001134872437},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.37040001153945923},{"id":"https://openalex.org/C2775945657","wikidata":"https://www.wikidata.org/wiki/Q381442","display_name":"Structuring","level":2,"score":0.3231000006198883},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.31200000643730164},{"id":"https://openalex.org/C2983449737","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Clinical diagnosis","level":2,"score":0.3059000074863434},{"id":"https://openalex.org/C146380142","wikidata":"https://www.wikidata.org/wiki/Q1137726","display_name":"Directed graph","level":2,"score":0.2824999988079071},{"id":"https://openalex.org/C2985722590","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medical knowledge","level":2,"score":0.274399995803833},{"id":"https://openalex.org/C3020132585","wikidata":"https://www.wikidata.org/wiki/Q2671652","display_name":"Diagnostic accuracy","level":2,"score":0.27379998564720154},{"id":"https://openalex.org/C154874363","wikidata":"https://www.wikidata.org/wiki/Q3518464","display_name":"Medical classification","level":2,"score":0.2712000012397766},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.25619998574256897}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11357158","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11357158","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":[],"awards":[{"id":"https://openalex.org/G649449356","display_name":null,"funder_award_id":"XRC-23027,XRC-23091","funder_id":"https://openalex.org/F4320325408","funder_display_name":"Fuzhou University"}],"funders":[{"id":"https://openalex.org/F4320325408","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2080133951","https://openalex.org/W2159583324","https://openalex.org/W2396881363","https://openalex.org/W2757504960","https://openalex.org/W2896538705","https://openalex.org/W3004001630","https://openalex.org/W3187228765","https://openalex.org/W4385245566","https://openalex.org/W4389520055","https://openalex.org/W4392503309"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"diagnosis":[1,59,75,145],"prediction":[2,60,76],"using":[3],"Electronic":[4],"Health":[5],"Records":[6],"(EHRs)":[7],"is":[8],"essential":[9],"for":[10,118,126],"personalized":[11],"healthcare.":[12],"Clinical":[13],"knowledge":[14],"graphs":[15],"(KGs)":[16],"can":[17],"enrich":[18],"EHRs":[19],"by":[20,87],"structuring":[21],"medical":[22,103],"knowledge,":[23],"and":[24,48,101,120,122,135],"recent":[25],"work":[26],"integrates":[27],"large":[28],"language":[29],"models":[30],"(LLMs)":[31],"with":[32,114],"KGs":[33],"to":[34,111],"enhance":[35],"reasoning.":[36],"However,":[37],"these":[38],"approaches":[39],"often":[40],"depends":[41],"on":[42,149],"static,":[43],"expensive":[44],"global":[45],"graph":[46,97,117,132],"construction":[47,107,133],"one-time":[49],"retrieval,":[50],"yielding":[51],"noisy":[52],"or":[53],"irrelevant":[54],"subgraphs":[55],"that":[56,78,155],"hinder":[57],"effective":[58],"in":[61,139,163,171],"real-world":[62,151,172],"clinical":[63,173],"scenarios.":[64],"To":[65],"this":[66],"end,":[67],"we":[68],"propose":[69],"<tex":[70],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[71,157],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\mathrm{D}^{2}$</tex>":[72],"KGMed,":[73],"a":[74,80],"framework":[77],"constructs":[79],"patient-specific":[81],"Dynamic":[82],"Diagnostic":[83],"Knowledge":[84],"Graph":[85],"guided":[86],"LLMs.":[88],"It":[89],"consists":[90],"of":[91],"two":[92,150],"stages:":[93],"constructing":[94],"an":[95],"initial":[96],"from":[98],"diagnostic":[99],"entities":[100],"multi-source":[102],"knowledge;":[104],"refining":[105],"its":[106,168],"via":[108],"supervised":[109],"fine-tuning":[110],"better":[112],"align":[113],"the":[115],"ideal":[116],"conciseness":[119],"relevance,":[121],"subsequently":[123],"leveraging":[124],"it":[125],"interpretable":[127],"predictions.":[128],"This":[129],"design":[130],"reduces":[131],"costs":[134],"retrieval":[136],"noise":[137],"common":[138],"KG+LLM":[140],"methods,":[141],"enabling":[142],"more":[143],"accurate":[144],"prediction.":[146],"Extensive":[147],"experiments":[148],"EHR":[152],"datasets":[153],"demonstrate":[154],"D<sup":[156],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>KGMed":[158],"outperforms":[159],"state-of-the-art":[160],"baselines,":[161],"especially":[162],"few-shot":[164],"learning":[165],"scenarios,":[166],"showcasing":[167],"practical":[169],"utility":[170],"settings.":[174]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-01-30T00:00:00"}
