{"id":6826,"date":"2026-01-15T10:31:36","date_gmt":"2026-01-15T09:31:36","guid":{"rendered":"https:\/\/dbis.rwth-aachen.de\/dbis\/?p=6826"},"modified":"2026-01-15T10:31:39","modified_gmt":"2026-01-15T09:31:39","slug":"comparative-analyses-of-hybrid-llms-with-knowledge-base-integration-and-rags-in-biomedical-domain","status":"publish","type":"post","link":"https:\/\/dbis.rwth-aachen.de\/dbis\/index.php\/2026\/comparative-analyses-of-hybrid-llms-with-knowledge-base-integration-and-rags-in-biomedical-domain\/","title":{"rendered":"Comparative analyses of hybrid LLMs with Knowledge base integration and RAGs in biomedical domain"},"content":{"rendered":"\n<p>Large language models (LLMs) are increasingly used in biomedical applications, including literature mining (PMID: 40188094), drug discovery (PMID: 38730226; 41362614; https:\/\/arxiv.org\/abs\/2510.27130), clinical decision support (PMID: 40753316), and patient data analysis (PMID: 41034564). Hybrid approaches combining LLMs with structured knowledge bases and retrieval-augmented generation (RAG) improve performance and interpretability (PMID: 38830083; https:\/\/www.biorxiv.org\/content\/10.1101\/2025.05.08.652829v2) . However, LLM-based systems remain vulnerable to hallucinations and generate associations that lack explicit evidence and traceability. This limits their reliability in high-stakes biomedical research. There is an urgent need for methods that systematically ground and validate LLM-derived associations using structured biomedical knowledge, such as knowledge graphs, to enable transparent, evidence-based discovery.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Large language models (LLMs) are increasingly used in biomedical applications, including literature mining (PMID: 40188094), drug discovery (PMID: 38730226; 41362614; https:\/\/arxiv.org\/abs\/2510.27130), clinical decision support (PMID: 40753316), and patient data analysis (PMID: 41034564). Hybrid approaches combining LLMs with structured knowledge bases and retrieval-augmented generation (RAG) improve performance and interpretability (PMID: 38830083; https:\/\/www.biorxiv.org\/content\/10.1101\/2025.05.08.652829v2) . However, LLM-based systems [&hellip;]<\/p>\n","protected":false},"author":19,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[21],"tags":[],"class_list":["post-6826","post","type-post","status-publish","format-standard","hentry","category-thesis"],"acf":[],"_links":{"self":[{"href":"https:\/\/dbis.rwth-aachen.de\/dbis\/index.php\/wp-json\/wp\/v2\/posts\/6826","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/dbis.rwth-aachen.de\/dbis\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/dbis.rwth-aachen.de\/dbis\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/dbis.rwth-aachen.de\/dbis\/index.php\/wp-json\/wp\/v2\/users\/19"}],"replies":[{"embeddable":true,"href":"https:\/\/dbis.rwth-aachen.de\/dbis\/index.php\/wp-json\/wp\/v2\/comments?post=6826"}],"version-history":[{"count":1,"href":"https:\/\/dbis.rwth-aachen.de\/dbis\/index.php\/wp-json\/wp\/v2\/posts\/6826\/revisions"}],"predecessor-version":[{"id":6827,"href":"https:\/\/dbis.rwth-aachen.de\/dbis\/index.php\/wp-json\/wp\/v2\/posts\/6826\/revisions\/6827"}],"wp:attachment":[{"href":"https:\/\/dbis.rwth-aachen.de\/dbis\/index.php\/wp-json\/wp\/v2\/media?parent=6826"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/dbis.rwth-aachen.de\/dbis\/index.php\/wp-json\/wp\/v2\/categories?post=6826"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/dbis.rwth-aachen.de\/dbis\/index.php\/wp-json\/wp\/v2\/tags?post=6826"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}