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English(EN) H3: A Healthcare Three-Hop Index for Physician Referral Network Prediction

新的H3索引通过三跳分析预测医生转诊网络

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了H3，一种新颖的医疗保健三跳索引，旨在改进医生转诊网络的预测。该方法通过中间医生对间接转诊路径进行建模，并结合基于度的归一化和冗余惩罚，以减少由中心节点主导的拓扑结构带来的噪声。使用Medicare数据进行的评估表明，H3在同期和时间转诊链接预测方面均优于现有的启发式方法和深度学习基线，提供了一种透明且可分解的解决方案。 AI

影响 通过实现对医生转诊模式更准确的预测，改善了医疗协调。

排序理由 这是一篇详细介绍预测医生转诊网络新方法的学术论文。[lever_c_demoted from research: ic=1 ai=0.4]

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 →

新的H3索引通过三跳分析预测医生转诊网络

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这是一篇详细介绍预测医生转诊网络新方法的学术论文。[lever_c_demoted from research: ic=1 ai=0.4]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Zhexi Gu, Jiaxin Ying, Xu-Wen Wang, Can Chen ·

    H3：面向医生推荐网络预测的医疗保健三跳索引

    arXiv:2605.02150v1 Announce Type: cross Abstract: Accurate prediction of physician referral links is essential for optimizing care coordination and reducing fragmentation in healthcare delivery. However, existing computational methods, ranging from triadic closure heuristics to g…

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