Multi-task deep latent spaces for cancer survival and drug sensitivity prediction.

ABSTRACT:

Motivation

Cancer is a very heterogeneous disease that can be difficult to treat without addressing the specific mechanisms driving tumour progression in a given patient. High-throughput screening and sequencing data from cancer cell-lines has driven many developments in drug development, however, there are important aspects crucial to precision medicine that are often overlooked, namely the inherent differences between tumours in patients and the cell-lines used to model them in vitro. Recent developments in transfer learning methods for patient and cell-line data have shown progress in translating results from cell-lines to individual patients in silico. However, transfer learning can be forceful and there is a risk that clinically relevant patterns in the omics profiles of patie

SUBMITTER: Rintala TJ 

PROVIDER: S-EPMC11520233 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature