Concepedia

Radiogenomics in Clear Cell Renal Cell Carcinoma: Machine Learning–Based High-Dimensional Quantitative CT Texture Analysis in Predicting <i>PBRM1</i> Mutation Status

Burak Koçak, Emine Şebnem Durmaz, Ece Ateş Kuş, Melis Baykara Ulusan

American Journal of Roentgenology · 2019 · 113 citations · 41 references

DOI

Abstract

ML-based high-dimensional quantitative CT texture analysis might be a feasible and potential method for predicting PBRM1 mutation status in patients with clear cell RCC.

References

41

SMOTE: Synthetic Minority Over-sampling Technique

Nitesh V. Chawla, Kevin W. Bowyer, Lawrence Hall et al. · Journal of Artificial Intelligence Research · 2002 · 29.6K citations · Full text

A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research

Terry K. Koo, Mae Y. Li · Journal of Chiropractic Medicine · 2016 · 25.4K citations · Full text

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Initial sequencing and analysis of the human genome

Eric S. Lander, Lauren Linton, Bruce W. Birren et al. · Nature · 2001 · 24.3K citations · Full text

Statistical Comparisons of Classifiers over Multiple Data Sets

Janez Demšar · 2006 · 11.2K citations

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Learning from Imbalanced Data

Haibo He, Edwardo A. Garcia · IEEE Transactions on Knowledge and Data Engineering · 2009 · 9.2K citations

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