English(EN) An unsupervised clustering analysis of breast cancer data derived from electronic health records enhanced through UMAP dimensionality reduction

UMAP和DBSCAN增强电子健康记录中的乳腺癌数据聚类

作者 PulseAugur 编辑部 · [1 个来源] · 2026-07-22 04:00

研究人员开发了一种新的方法，利用电子健康记录中的乳腺癌数据进行无监督聚类分析。该方法结合了用于降维的均匀流形逼近与投影（UMAP）和DBSCAN聚类算法。该组合方法的有效性通过DBCV、DCSI和DISCO等统计指标进行了验证，证明了其识别具有医学意义的患者群体的潜力。 AI

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arXiv cs.LG TIER_1 English(EN) · Davide Chicco, Nicoletta Benvenuto · 2026-07-22 04:00

基于电子健康记录的乳腺癌数据无监督聚类分析，通过UMAP降维技术增强

arXiv:2607.19089v1 Announce Type: new Abstract: Breast cancer is one of the most widespread types of cancer, affecting approximately 8 million women worldwide. Electronic health records of patients diagnosed with this disease can serve as valuable datasets for computational analy…

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基于电子健康记录的乳腺癌数据无监督聚类分析，通过UMAP降维技术增强

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