Thesis of Thomas Ranvier


Subject:
Deep multi-view learning for immunotherapy post-treatment of cancer patients

Defense date: 06/12/2023

Advisor: Khalid Benabdeslem
Coadvisor: Emmanuel Coquery, Haytham Elghazel

Summary:

This thesis is part of the European project Qualitop, which aims to improve the quality of life of cancer patients treated with immunotherapy.
The objective of the thesis will be to predict the side effects that a patient is most likely to develop upon starting an immunotherapy treatment.
We are exploring and employing deep machine learning to complement the health data collected for the project, we wish to explore the possibilities of data augmentation and balancing using GANs, and finally, to design an original prediction approach effective in the health domain.


Jury:
Mme Boudjeloud-Assala LydiaMaître de conférenceUniversité de LorraineRapporteur(e)
M. Quafafou MohamedProfesseur(e)Université d’Aix-MarseilleRapporteur(e)
Mme Benbernou SalimaProfesseur(e)Université Paris-DescartesExaminateur​(trice)
M. Grozavu Nistor (Professeur, ) - ExaminateuProfesseur(e)Université CergyExaminateur​(trice)
Mme Maucourt-Boulch DelphineProfesseur(e)UCBL HCLEncadrant(e)
M. Benabdeslem KhalidMaître de conférenceLIRIS CNRS UMR 5205 - Université Claude Bernard Lyon 1Directeur(trice) de thèse
M. Coquery EmmanuelMaître de conférenceLIRIS - CNRS UMR 5205 - Université Claude Bernard Lyon 1Co-encadrant(e)
M. Elghazel HaythamMaître de conférenceLIRIS - CNRS UMR 5205 - Université Claude Bernard Lyon 1Co-encadrant(e)