本研究针对神经母细胞瘤(NB)患者电子健康记录(EHRs)的异质性难题，创新性应用密度聚类算法DBSCAN结合DBCV验证指标，成功从三个开放数据集中识别出具有临床意义的患者亚群。研究人员通过分析Genoa、Shanghai和TARGET-NBL数据集，发现MYCN扩增、风险分级等关键变量可 ...

推荐：本研究针对传统Artifact Subspace Reconstruction (ASRoriginal )算法在复杂运动任务（如三球杂耍）中因高频运动伪迹导致的校准数据质量低下问题，提出基于DBSCAN（密度聚类）和GEV（广义极值分布）的改进方法ASRDBSCAN 和ASRGEV 。通过模拟与真实脑电数据验证，新方法 ...

A good way to see where this article is headed is to take a look at the screenshot in Figure 1 and the graph in Figure 2. The demo program begins by loading a tiny 10-item dataset into memory. The ...

Compared to other clustering techniques, DBSCAN does not require you to explicitly specify how many data clusters to use, explains Dr. James McCaffrey of Microsoft Research in this full-code, ...