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 Lydia | Maître de conférence | Université de Lorraine | Rapporteur(e) |
| M. Quafafou Mohamed | Professeur(e) | Université d’Aix-Marseille | Rapporteur(e) |
| Mme Benbernou Salima | Professeur(e) | Université Paris-Descartes | Examinateur(trice) |
| M. Grozavu Nistor (Professeur, ) - Examinateu | Professeur(e) | Université Cergy | Examinateur(trice) |
| Mme Maucourt-Boulch Delphine | Professeur(e) | UCBL HCL | Encadrant(e) |
| M. Benabdeslem Khalid | Maître de conférence | LIRIS CNRS UMR 5205 - Université Claude Bernard Lyon 1 | Directeur(trice) de thèse |
| M. Coquery Emmanuel | Maître de conférence | LIRIS - CNRS UMR 5205 - Université Claude Bernard Lyon 1 | Co-encadrant(e) |
| M. Elghazel Haytham | Maître de conférence | LIRIS - CNRS UMR 5205 - Université Claude Bernard Lyon 1 | Co-encadrant(e) |