- 文章转自微信公众号：机器学习炼丹术
- 笔记：陈亦新
- 参考论文: Correlation Between dual-time-point FDG PET and Tumor Microenvironment Immune Types in Non-small cell lung Cancer
这一篇和深度学习其实关系不大，目的还是学习dual-time-point和一些统计方法。
method概述
本文retrospective回顾性分析了91例病人。分解计算了metabolic parameters （MPs），包含：
- early scan：eSUVmax，eSUVmean，eMTV，eTLG
- delay scan也是这四个参数
- 还计算了两个时间点之间的MPs，DSUVmax，DSUVmean，DMTV，DTLG。
statistical analysis
- the distribution of variable was checked using Shapiro-Wilk test
- For continuous data, the differences between two groups were assessed using Mann-Whitney U test or Student's t-test
- Differences among multi-group were compared using one-way analysis of variance (ANOVA) or Kruskal-Walls H test
MTV and TLG
- MTV：metabolic tumor volume
- TLG：total lesion glycolysis
- Shapiro-Wilk test：进行正态分布的检验
- Mann-Whitney U test， MWW检验，对独立样本进行的一种不要求正态分布的t-test检验方式。主要对来自除了总体均值外完全相同的两个总体，检验其是否显著差异。
- ANOVA是方差分析的方法，用来解决多组样本之间的平均值是否有显著差异的问题。
