Multimodal integration of longitudinal noninvasive diagnostics for survival prediction in immunotherapy using deep learning.

ABSTRACT:

Objectives

Immunotherapies have revolutionized the landscape of cancer treatments. However, our understanding of response patterns in advanced cancers treated with immunotherapy remains limited. By leveraging routinely collected noninvasive longitudinal and multimodal data with artificial intelligence, we could unlock the potential to transform immunotherapy for cancer patients, paving the way for personalized treatment approaches.

Materials and methods

In this study, we developed a novel artificial neural network architecture, multimodal transformer-based simple temporal attention (MMTSimTA) network, building upon a combination of recent successful developments. We integrated pre- and on-treatment blood measurements, prescribed medications, and CT-based volumes of organs fr

SUBMITTER: Yeghaian M 

PROVIDER: S-EPMC12277703 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature