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English(EN) Automated Chest CT Protocol Selection via Large Language Model Derived Text Embeddings from Imaging Request Text

大型语言模型准确地从临床文本中选择胸部CT方案

研究人员开发了一个决策支持系统,该系统使用大型语言模型(LLM)来自动选择胸部CT方案。该系统利用临床影像请求的文本嵌入,旨在通过解决当前方案选择方法的手动和不一致性来提高诊断质量和患者安全。基于LLM的方法表现出强大的性能,在18种CT方案中整体准确率为79%,在独立病例上的准确性与放射科医生相当,表明其有潜力成为未来方案推荐工具的基础。 AI

影响 这项研究展示了大型语言模型在提高医学影像方案选择效率和准确性方面的潜力,可能带来更好的患者预后。

排序理由 详细介绍大型语言模型在医学领域新应用的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

大型语言模型准确地从临床文本中选择胸部CT方案

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详细介绍大型语言模型在医学领域新应用的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Zahra Hosseini, Mahan Pouromidi, Farzad Khalvati, Patrik Rogalla ·

    基于大型语言模型生成的影像请求文本嵌入的自动胸部CT协议选择

    arXiv:2609.07986v1 Announce Type: new Abstract: Purpose: Accurate CT protocol selection is critical for diagnostic quality and patient safety, yet the current process is manual, time-consuming, and prone to inconsistencies. Prior Machine Learning methods using keywords or bag-of-…