Ndèye Maguette Mbaye
Armines
Advisor: Chloé-Agathe Azencott
Project description
The goal of this project is to develop and apply novel machine learning techniques to predict cancer outcome (for example, recurrence or survival) from multi-modal patient data (including, medical notes in natural languages and the outcome of various lab analyses, and multiple genomic data modalities, such as copy number variation, gene expression or epigenetic data). I will investigate mathematical and computational frameworks to represent and learn from such heterogeneous data, and apply them on real data available through collaborations with cancer hospitals.
Secondments
- Learning from multimodal health data for improved Depression treatment
Host: Max Planck Institute of Psychiatry
Planned date: November 2020 – January 2021 - Inferring causal relations from health records
Host: IBM
Planned date: December 2021 – February 2022
Machine Learning Frontiers in Precision Medicine 