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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...
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 |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
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 |
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