What is it about?
In this work we have tried to calculate and identify quantitative imaging features (radiomics) that can be used in a machine learning model to predict risk of cancer recurrence for lung cancer patients that have gone through surgical resection of tumor tissue.
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Why is it important?
It is important to predict whether a patient will have cancer recurrence or not, because this information can help the physician to make a better decision in treatment of the patient.
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This page is a summary of: Fusion of Quantitative Image and Genomic Biomarkers to Improve Prognosis Assessment of Early Stage Lung Cancer Patients, IEEE Transactions on Biomedical Engineering, May 2016, Institute of Electrical & Electronics Engineers (IEEE),
DOI: 10.1109/tbme.2015.2477688.
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