Outcome Prediction at Patient Level Derived from Pre-Treatment 18F-FDG PET Due to Machine Learning in Metastatic Melanoma Treated with Anti-PD1 Treatment

Outcome Prediction at Patient Level Derived from Pre-Treatment 18F-FDG PET Due to Machine Learning in Metastatic Melanoma Treated with Anti-PD1 Treatment

(1) Background: As outcome of patients with metastatic melanoma treated with anti-PD1 immunotherapy can vary in success, predictors are needed. We aimed to predict at the patients’ levels, overall survival (OS) and progression-free survival (PFS) after one year of immunotherapy, based on their pre-t...

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Bibliographic Details
Main Authors: Anthime Flaus, Vincent Habouzit, Nicolas de Leiris, Jean-Philippe Vuillez, Marie-Thérèse Leccia, Mathilde Simonson, Jean-Luc Perrot, Florent Cachin, Nathalie Prevot
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Diagnostics
Subjects:
18F-FDG PET
radiomics
machine-learning
immunotherapy
melanoma
prediction
Online Access:https://www.mdpi.com/2075-4418/12/2/388

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https://www.mdpi.com/2075-4418/12/2/388

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