Development and Validation Of The Large Nodule Radiomics Predictive Vector (LN-RPV)

Development and Validation Of The Large Nodule Radiomics Predictive Vector (LN-RPV)

Large lung nodules are not currently stratified well by existing clinical guidelines. Here we provide the data needed to generate the 'large nodule radiomics predictive vector' as described in 'A Radiomics-Based Decision Support Tool Improves Lung Cancer Diagnosis In Combination With...

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description Large lung nodules are not currently stratified well by existing clinical guidelines. Here we provide the data needed to generate the 'large nodule radiomics predictive vector' as described in 'A Radiomics-Based Decision Support Tool Improves Lung Cancer Diagnosis In Combination With The Herder Score in Large Lung Nodules', published in EBioMedicine. This model is able to classify large lung nodules according to cancer risk. The radiomics features were extracted from manual nodule segmentations using TexLab 2.0. The 'Outcome' column refers to the cancer status of the nodule (0: benign, 1: malignant). Access to the source images or clinicodemographic data will be considered on request to Dr. Richard Lee (richard.lee@rmh.nhs.uk).
doi_str_mv 10.17632/rz72hs5dvg
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title Development and Validation Of The Large Nodule Radiomics Predictive Vector (LN-RPV)
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