This workshop will explore the latest approaches to medical knowledge systems, with a focus on the synergy between large language models, retrieval-augmented generation, and foundation/agentic models. The workshop will promote interdisciplinary collaboration among researchers, practitioners, and clinicians to advance evidence-driven AI in healthcare. Topics will include knowledge-grounded question answering, biomedical document retrieval, multimodal clinical reasoning, personalization, safety, and the challenges of deploying AI in practice. With a strong emphasis on reproducibility, evaluation, and responsible application in clinical settings, the workshop will define the next frontier of knowledge-centric AI in medicine.
Advances in Medical Knowledge Systems: LLMs, RAG and Foundation Models / Di Teodoro, G., Guarrasi, V., Siciliano, F., Silvestri, F.. - (2025), pp. 6901-6904. (34th ACM International Conference on Information and Knowledge Management (CIKM 2025) Seoul, Republic of Korea ) [10.1145/3746252.3761592].
Advances in Medical Knowledge Systems: LLMs, RAG and Foundation Models
Giulia Di Teodoro
;Valerio Guarrasi;Federico Siciliano;Fabrizio Silvestri
2025
Abstract
This workshop will explore the latest approaches to medical knowledge systems, with a focus on the synergy between large language models, retrieval-augmented generation, and foundation/agentic models. The workshop will promote interdisciplinary collaboration among researchers, practitioners, and clinicians to advance evidence-driven AI in healthcare. Topics will include knowledge-grounded question answering, biomedical document retrieval, multimodal clinical reasoning, personalization, safety, and the challenges of deploying AI in practice. With a strong emphasis on reproducibility, evaluation, and responsible application in clinical settings, the workshop will define the next frontier of knowledge-centric AI in medicine.| File | Dimensione | Formato | |
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DiTeodoro_Advances-in-Medical_2025.pdf
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Note: https://dl.acm.org/doi/10.1145/3746252.3761592
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