A precise grading method for glioma based on radiomics

Grading of gliomas is important both in treatment decision and assessment of prognosis. The new solution provided by the authors has fast, simple, and non-invasive advantages based on radiomics. This paper calculated 346 radiomics' features, performed dimension reduction using elastic net, and implemented grading with logistic regress model. After conducting experiment on 161 glioma samples from the Henan Provincial People's Hospital between 2012 and 2016, this study finds that the result shows good grading effect. What is more, the sensitivity is 96.33%, specificity is 73.08%, false positive rate is 26.92%, AUC is 94.94%, and accuracy is 88.82%.

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