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English(EN) COTCAgent: Preventive Consultation via Probabilistic Chain-of-Thought Completion

COTCAgent 改进了 LLM 对患者健康记录的分析

研究人员开发了 COTCAgent,这是一个旨在改进大型语言模型分析纵向电子健康记录方式的新框架。该代理通过结合统计推理和处理非均匀时间序列数据来解决当前模型的局限性,以更好地捕捉长程时间依赖性。COTCAgent 使用时间统计适配器进行数据处理,并使用思维链补全层进行疾病风险评估,在自建数据集和 HealthBench 数据集上取得了高精度。 AI

影响 增强了 LLM 在医疗数据分析中的能力,可能改进临床决策支持系统。

排序理由 发表了一篇详细介绍新框架及其在基准测试中表现的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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

COTCAgent 改进了 LLM 对患者健康记录的分析

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发表了一篇详细介绍新框架及其在基准测试中表现的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Chuanzhi Xu ·

    COTCAgent:通过概率性思维链补全进行预防性咨询

    As large language models empower healthcare, intelligent clinical decision support has developed rapidly. Longitudinal electronic health records (EHR) provide essential temporal evidence for accurate clinical diagnosis and analysis. However, current large language models have cri…