A Clinical Prognostic Model Based on Machine Learning from the Fondazione Italiana Linfomi (FIL) MCL0208 Phase III Trial

A Clinical Prognostic Model Based on Machine Learning from the Fondazione Italiana Linfomi (FIL) MCL0208 Phase III Trial

Background: Multicenter clinical trials are producing growing amounts of clinical data. Machine Learning (ML) might facilitate the discovery of novel tools for prognostication and disease-stratification. Taking advantage of a systematic collection of multiple variables, we developed a model derived...

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Bibliographic Details
Main Authors: Gian Maria Zaccaria, Simone Ferrero, Eva Hoster, Roberto Passera, Andrea Evangelista, Elisa Genuardi, Daniela Drandi, Marco Ghislieri, Daniela Barbero, Ilaria Del Giudice, Monica Tani, Riccardo Moia, Stefano Volpetti, Maria Giuseppina Cabras, Nicola Di Renzo, Francesco Merli, Daniele Vallisa, Michele Spina, Anna Pascarella, Giancarlo Latte, Caterina Patti, Alberto Fabbri, Attilio Guarini, Umberto Vitolo, Olivier Hermine, Hanneke C Kluin-Nelemans, Sergio Cortelazzo, Martin Dreyling, Marco Ladetto
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Cancers
Subjects:
machine-learning
mantle cell lymphoma
prognostication
Online Access:https://www.mdpi.com/2072-6694/14/1/188

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https://www.mdpi.com/2072-6694/14/1/188

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