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Updated: Sep 9, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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专用大型语言模型与CT和MRI放射学GPT-4o的比较报告摘要

Sunyi Zheng1, Nannan Zhao2, Jing Wang3

  • 1Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin Key Laboratory of Digestive Cancer, Key Laboratory of Cancer Prevention and Therapy, Department of Radiology, West Huan-Hu Rd, Ti Yuan Bei, Hexi District, 300060 Tianjin, China.

Radiology
|September 2, 2025
PubMed
概括

一个专门用于放射学报告总结的大型语言模型 (LLM) 超过了通用GPT-4o. 在生成准确和临床有用的放射学报告摘要方面,LLM-RadSum表现出卓越的表现.

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