A Machine Learning Approach for High-Dimensional Time-to-Event Prediction With Application to Immunogenicity of Biotherapies in the ABIRISK Cohort

A Machine Learning Approach for High-Dimensional Time-to-Event Prediction With Application to Immunogenicity of Biotherapies in the ABIRISK Cohort

Predicting immunogenicity for biotherapies using patient and drug-related factors represents nowadays a challenging issue. With the growing ability to collect massive amount of data, machine learning algorithms can provide efficient predictive tools. From the bio-clinical data collected in the multi...

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Bibliographic Details
Main Authors: Julianne Duhazé, Signe Hässler, Delphine Bachelet, Aude Gleizes, Salima Hacein-Bey-Abina, Matthieu Allez, Florian Deisenhammer, Anna Fogdell-Hahn, Xavier Mariette, Marc Pallardy, Philippe Broët
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-04-01
Series:Frontiers in Immunology
Subjects:
immunogenicity
biotherapy
machine learning
survival random forest
prediction
Online Access:https://www.frontiersin.org/article/10.3389/fimmu.2020.00608/full

Internet

https://www.frontiersin.org/article/10.3389/fimmu.2020.00608/full

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