18FDG PET/CT and Machine Learning for the prediction of lung cancer response to immunotherapy

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18FDG PET/CT and Machine Learning for the prediction of lung cancer response to immunotherapy

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Schmutz, Hugo | Mattei, Pierre-Alexandre | Contu, Sara | Chardin, David | Humbert, Olivier

Edité par CCSD -

International audience. In patients with non-small cell lung cancer (NSCLC) treated with immunotherapy, individual biological and PET imaging prognostic biomarkers have been recently identified. However, combination of biomarkers has not been studied yet. The purpose of this study is to combine clinical, biological and 18FDG PET/CT parameters and use machine-learning algorithms to build more accurate prognostic models of NSCLC response to immunotherapy

Langue: en

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