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ENTAgents: AI Agents for Complex Knowledge Otolaryngology
2025-01-07
otolaryngology
Title + abstract only
View on medRxiv
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Various healthcare applications based on large language models (LLMs) have emerged as LLMs show improved efficiency and error reduction. Recently, retrieval augmented generation (RAG) has been adopted frequently for LLM applications to solve the problem of hallucinations. Despite the success of RAG, it has its drawbacks, including incomplete semantic meanings, and large-scale dataset requirements. AI Agents have shown great potential in medicine and healthcare applications by leveraging their ri...
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