{"id":"https://openalex.org/W7125976397","doi":"https://doi.org/10.4108/eetpht.11.11670","title":"Enhancing Medical Question-Answering Systems with Knowledge Graph-Integrated Large Language Models: A Comparative Analysis","display_name":"Enhancing Medical Question-Answering Systems with Knowledge Graph-Integrated Large Language Models: A Comparative Analysis","publication_year":2026,"publication_date":"2026-01-28","ids":{"openalex":"https://openalex.org/W7125976397","doi":"https://doi.org/10.4108/eetpht.11.11670"},"language":"en","primary_location":{"id":"doi:10.4108/eetpht.11.11670","doi":"https://doi.org/10.4108/eetpht.11.11670","is_oa":true,"landing_page_url":"https://doi.org/10.4108/eetpht.11.11670","pdf_url":"https://publications.eai.eu/index.php/phat/article/download/11670/3887","source":{"id":"https://openalex.org/S2736858385","display_name":"EAI Endorsed Transactions on Pervasive Health and Technology","issn_l":"2411-7145","issn":["2411-7145"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","poland-20","russia-white-list-2"],"host_organization":"https://openalex.org/P4310321144","host_organization_name":"Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","host_organization_lineage":["https://openalex.org/P4310321144"],"host_organization_lineage_names":["Institute for Computer Sciences, Social Informatics and Telecommunications Engineering"],"type":"journal"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EAI Endorsed Transactions on Pervasive Health and Technology","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://publications.eai.eu/index.php/phat/article/download/11670/3887","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5111038677","display_name":"Jiaxu Lin","orcid":"https://orcid.org/0009-0007-5661-0165","observed_orcids":["https://orcid.org/0009-0007-5661-0165"]},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jiaxu Lin","raw_affiliation_strings":["UNSW Sydney"],"raw_orcid":"https://orcid.org/0009-0007-5661-0165","affiliations":[{"raw_affiliation_string":"UNSW Sydney","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124054926","display_name":"Silin Ouyang","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Silin Ouyang","raw_affiliation_strings":["Guangzhou University of Software"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangzhou University of Software","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"11","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":0.6195999979972839,"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":0.6195999979972839,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.21580000221729279,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.06669999659061432,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"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/medical-question-answering","display_name":"medical question answering","score":0.9769999980926514},{"id":"https://openalex.org/keywords/large-language-models","display_name":"large language models","score":0.9909999966621399},{"id":"https://openalex.org/keywords/named-entity-recognition","display_name":"named entity recognition","score":0.9580000042915344},{"id":"https://openalex.org/keywords/wikipedia-knowledge-base","display_name":"Wikipedia knowledge base","score":0.906000018119812},{"id":"https://openalex.org/keywords/factual-accuracy","display_name":"factual accuracy","score":0.6389999985694885},{"id":"https://openalex.org/keywords/semantic-coherence","display_name":"semantic coherence","score":0.5040000081062317}],"concepts":[{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.802299976348877},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7056999802589417},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6391000151634216},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.6019999980926514},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.6014000177383423},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5153999924659729},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5023999810218811},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4932999908924103},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4537000060081482},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4122999906539917},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.41119998693466187},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.3903000056743622},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.3887999951839447},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3732999861240387},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.3619000017642975},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3224000036716461},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.301800012588501},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.29350000619888306},{"id":"https://openalex.org/C2985722590","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medical knowledge","level":2,"score":0.29280000925064087},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.2809999883174896},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2806999981403351},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.26989999413490295},{"id":"https://openalex.org/C115925183","wikidata":"https://www.wikidata.org/wiki/Q1412694","display_name":"Knowledge-based systems","level":2,"score":0.26829999685287476},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.2669000029563904}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.4108/eetpht.11.11670","doi":"https://doi.org/10.4108/eetpht.11.11670","is_oa":true,"landing_page_url":"https://doi.org/10.4108/eetpht.11.11670","pdf_url":"https://publications.eai.eu/index.php/phat/article/download/11670/3887","source":{"id":"https://openalex.org/S2736858385","display_name":"EAI Endorsed Transactions on Pervasive Health and Technology","issn_l":"2411-7145","issn":["2411-7145"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","poland-20","russia-white-list-2"],"host_organization":"https://openalex.org/P4310321144","host_organization_name":"Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","host_organization_lineage":["https://openalex.org/P4310321144"],"host_organization_lineage_names":["Institute for Computer Sciences, Social Informatics and Telecommunications Engineering"],"type":"journal"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EAI Endorsed Transactions on Pervasive Health and Technology","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.4108/eetpht.11.11670","doi":"https://doi.org/10.4108/eetpht.11.11670","is_oa":true,"landing_page_url":"https://doi.org/10.4108/eetpht.11.11670","pdf_url":"https://publications.eai.eu/index.php/phat/article/download/11670/3887","source":{"id":"https://openalex.org/S2736858385","display_name":"EAI Endorsed Transactions on Pervasive Health and Technology","issn_l":"2411-7145","issn":["2411-7145"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","poland-20","russia-white-list-2"],"host_organization":"https://openalex.org/P4310321144","host_organization_name":"Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","host_organization_lineage":["https://openalex.org/P4310321144"],"host_organization_lineage_names":["Institute for Computer Sciences, Social Informatics and Telecommunications Engineering"],"type":"journal"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EAI Endorsed Transactions on Pervasive Health and Technology","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7125976397.pdf","grobid_xml":"https://content.openalex.org/works/W7125976397.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391226472","https://openalex.org/W7127398953","https://openalex.org/W7124283542","https://openalex.org/W7166843117","https://openalex.org/W4416034803","https://openalex.org/W7126107474","https://openalex.org/W7169541044","https://openalex.org/W7133233753","https://openalex.org/W4392736985","https://openalex.org/W4404356426"],"abstract_inverted_index":{"This":[0],"study":[1],"investigates":[2],"the":[3,17,34,41,48,55,62],"impact":[4],"of":[5,19,36,43,50,58,76],"integrating":[6,124],"knowledge":[7,56,126],"graph":[8],"prompt":[9],"engineering":[10],"(KGPE)":[11],"with":[12],"large":[13],"language":[14],"models":[15],"in":[16,135],"context":[18],"medical":[20,38,136],"question":[21],"answering.":[22],"The":[23,83],"Hugging":[24],"Face":[25],"MedQA":[26],"dataset":[27],"(N":[28],"=":[29],"5,000)":[30],"was":[31],"utilised":[32],"for":[33],"extraction":[35],"key":[37],"entities":[39],"via":[40],"implementation":[42],"named":[44],"entity":[45],"recognition,":[46],"and":[47,68,79,99,132],"construction":[49],"SPARQL-based":[51],"relational":[52],"prompts":[53],"from":[54,94,103],"base":[57],"Wikipedia":[59],"to":[60,96,105,117],"guide":[61],"reasoning":[63,137],"process.":[64],"Two":[65],"models,":[66],"Llama-2-7B-chat-hf":[67,109],"Qwen-2-7B-Instruct,":[69],"are":[70],"evaluated":[71],"through":[72,127],"a":[73,111],"weighted":[74],"aggregation":[75],"BLEU,":[77],"ROUGE,":[78],"cosine":[80,100],"similarity":[81,101],"metrics.":[82],"findings":[84,121],"demonstrate":[85,122],"that":[86,123],"Qwen-2-7B-Instruct":[87],"attains":[88],"substantial":[89],"enhancements":[90],"under":[91],"KGPE\u2014BLEU":[92],"escalating":[93],"0.366":[95],"0.531":[97],"(+0.165)":[98],"rising":[102],"0.763":[104],"0.820":[106],"(+0.057).":[107],"Conversely,":[108],"exhibits":[110],"modest":[112],"decrease,":[113],"signifying":[114],"divergent":[115],"responsiveness":[116],"structured":[118,125],"knowledge.":[119],"These":[120],"KGPE":[128],"enhances":[129],"factual":[130],"accuracy":[131],"semantic":[133],"coherence":[134],"without":[138],"modifying":[139],"model":[140],"architecture":[141]},"counts_by_year":[],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2026-01-29T00:00:00"}