- 文章转自微信大众号:机器学习炼丹术
- 笔记:陈亦新
- 参阅论文: 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,意图还是学习dual-time-point和一些统计方法。
method概述
本文retrospective回忆性分析了91例病人。分解计算了metabolic parameters (MPs),包括:
- early scan:eSUVmax,eSUVmean,eMTV,eTLG
- delay scan也是这四个参数
- 还计算了两个时刻点之间的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:进行正态分布的查验
- Mann-Whitney U test, MWW查验,对独立样本进行的一种不要求正态分布的t-test查验方法。主要对来自除了整体均值外完全相同的两个整体,查验其是否明显差异。
- 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明显差异的问题。