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Radiomics approach for survival prediction in chronic obstructive pulmonary disease.

Young Hoon ChoJoon Beom SeoSang Min LeeNamkug KimJihye YunJeong Eun HwangJae Seung LeeYeon-Mok OhSang Do LeeLi-Cher LohChoo-Khoom Ong
Published in: European radiology (2021)
• A total of 525 chest CT-based radiomics features were extracted and the five radiomics features of %LAA-950, AWT_Pi10_6th, AWT_Pi10_heterogeneity, %WA_heterogeneity, and VA18mm were selected to generate a radiomics model. • A radiomics model for predicting survival of COPD patients demonstrated reliable performance with a C-index of 0.774 in the discovery group and 0.805 in the validation group. • Radiomics approach was able to effectively identify COPD patients with an increased risk of mortality, and patients assigned to the high-risk group demonstrated worse overall survival in both the discovery and validation groups.
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