放射基因组学
医学
无线电技术
特征选择
选择(遗传算法)
变量(数学)
透视图(图形)
重症监护医学
机器学习
人工智能
计算机科学
放射科
数学
数学分析
作者
Yuan Cheng,Ran Huang,Yang Wang
标识
DOI:10.1016/j.jtho.2023.10.015
摘要
We have read with great interest the newly published article by Chen et al.,1 in which the authors developed a novel, noninvasive, radiogenomics composite biomarker for predicting programmed death ligand 1 positivity, disease response, and pneumonitis occurrence in NSCLC. Here, we like to draw attention to some important points regarding the optimal choice of parameter and variable in the development of radiomics signatures, including one error in the original article from the perspective of radiologists.
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