Development of survival predictors for high-grade serous ovarian cancer based on stable radiomic features from computed tomography images

Author:

Hu Jiaqi,Wang Zhiwu,Zuo Ruocheng,Zheng Chengcai,Lu Bingjian,Cheng Xiaodong,Lu Weiguo,Zhao Chunhui,Liu Pengyuan,Lu Yan

Publisher

Elsevier BV

Subject

Multidisciplinary

Reference27 articles.

1. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach;Aerts;Nat. Commun.,2014

2. Rethinking ovarian cancer II: reducing mortality from high-grade serous ovarian cancer;Bowtell;Nat. Rev. Cancer,2015

3. Cancer statistics in China, 2015;Chen;CA A Cancer J. Clin.,2016

4. Solutions to instability problems with sequential wrapper-based approaches to feature selection;Dunne;J. Mach. Learn. Res.,2002

5. Statistical primer: multivariable regression considerations and pitfalls;Grant;Eur. J. Cardio Thorac.,2019

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