Machine Learning Using Real-World and Translational Data to Improve Treatment Selection for NSCLC Patients Treated with Immunotherapy

Machine Learning Using Real-World and Translational Data to Improve Treatment Selection for NSCLC Patients Treated with Immunotherapy

(1) Background: In advanced non-small cell lung cancer (aNSCLC), programmed death ligand 1 (PD-L1) remains the only biomarker for candidate patients to immunotherapy (IO). This study aimed at using artificial intelligence (AI) and machine learning (ML) tools to improve response and efficacy predicti...

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Bibliographic Details
Main Authors: Arsela Prelaj, Mattia Boeri, Alessandro Robuschi, Roberto Ferrara, Claudia Proto, Giuseppe Lo Russo, Giulia Galli, Alessandro De Toma, Marta Brambilla, Mario Occhipinti, Sara Manglaviti, Teresa Beninato, Achille Bottiglieri, Giacomo Massa, Emma Zattarin, Rosaria Gallucci, Edoardo Gregorio Galli, Monica Ganzinelli, Gabriella Sozzi, Filippo G. M. de Braud, Marina Chiara Garassino, Marcello Restelli, Alessandra Laura Giulia Pedrocchi, Francesco Trovo'
Format: Article
Language:English
Published: MDPI AG 2022-01-01
Series:Cancers
Subjects:
non-small cell lung cancer
immunotherapy
biomarker
artificial intelligence
machine learning
Online Access:https://www.mdpi.com/2072-6694/14/2/435

Internet

https://www.mdpi.com/2072-6694/14/2/435

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