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222P A hybrid text-knowledge graph retrieval-augmented generation system for clinical decision support in soft tissue sarcoma

A study on a hybrid text-knowledge graph retrieval-augmented generation system for clinical decision support.

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222P A hybrid text-knowledge graph retrieval-augmented generation system for clinical decision support in soft tissue sarcoma

By C. Yang, Y. Chu, C. Hua, Franka Menge, Christoph Reissfelder, B. Kasper, C. Li, Julia JakobESMO rare cancers.
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The study presents a system that combines text and knowledge graphs to aid in clinical decision-making. It focuses on soft tissue sarcoma, analyzing proteomic data from patient samples. The analysis highlights potential pathways for further investigation and identifies potential drug candidates.

Abstract

The study presents a system that combines text and knowledge graphs to aid in clinical decision-making. It focuses on soft tissue sarcoma, analyzing proteomic data from patient samples. The analysis highlights potential pathways for further investigation and identifies potential drug candidates.

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hybrid-systemtext-knowledge-graphclinical-decision-supportproteomic-analysissoft-tissue-sarcomaKnowledge GraphsContent EngineeringAI AgentsSemantic Interoperability
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