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

SIMPLE SUMMARY: In this paper, the authors show that artificial intelligence (AI) and machine learning (ML) are useful approaches to integrate multifactorial data and helpful for personalized prediction. In detail, compared to PD-L1 for advanced non-small cell lung cancer (NSCLC), ML tools predicted...

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Detalles Bibliográficos
Autores principales: Prelaj, Arsela, Boeri, Mattia, Robuschi, Alessandro, Ferrara, Roberto, Proto, Claudia, Lo Russo, Giuseppe, Galli, Giulia, De Toma, Alessandro, Brambilla, Marta, Occhipinti, Mario, Manglaviti, Sara, Beninato, Teresa, Bottiglieri, Achille, Massa, Giacomo, Zattarin, Emma, Gallucci, Rosaria, Galli, Edoardo Gregorio, Ganzinelli, Monica, Sozzi, Gabriella, de Braud, Filippo G. M., Garassino, Marina Chiara, Restelli, Marcello, Pedrocchi, Alessandra Laura Giulia, Trovo', Francesco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8773718/
https://www.ncbi.nlm.nih.gov/pubmed/35053597
http://dx.doi.org/10.3390/cancers14020435

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8773718/
https://www.ncbi.nlm.nih.gov/pubmed/35053597
http://dx.doi.org/10.3390/cancers14020435

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