Multimodal data fusion for cancer biomarker discovery with deep learning

S Steyaert, M Pizurica, D Nagaraj… - Nature machine …, 2023 - nature.com
Technological advances have made it possible to study a patient from multiple angles with
high-dimensional, high-throughput multiscale biomedical data. In oncology, massive …

The biological meaning of radiomic features

MR Tomaszewski, RJ Gillies - Radiology, 2021 - pubs.rsna.org
Radiomic analysis offers a powerful tool for the extraction of clinically relevant information
from radiologic imaging. Radiomics can be used to predict patient outcome through …

The University of Pennsylvania glioblastoma (UPenn-GBM) cohort: advanced MRI, clinical, genomics, & radiomics

S Bakas, C Sako, H Akbari, M Bilello, A Sotiras… - Scientific data, 2022 - nature.com
Glioblastoma is the most common aggressive adult brain tumor. Numerous studies have
reported results from either private institutional data or publicly available datasets. However …

The applications of radiomics in precision diagnosis and treatment of oncology: opportunities and challenges

Z Liu, S Wang, D Dong, J Wei, C Fang, X Zhou… - …, 2019 - pmc.ncbi.nlm.nih.gov
Medical imaging can assess the tumor and its environment in their entirety, which makes it
suitable for monitoring the temporal and spatial characteristics of the tumor. Progress in …

Enhancing NSCLC recurrence prediction with PET/CT habitat imaging, ctDNA, and integrative radiogenomics-blood insights

SJ Sujit, M Aminu, TV Karpinets, P Chen… - Nature …, 2024 - nature.com
While we recognize the prognostic importance of clinicopathological measures and
circulating tumor DNA (ctDNA), the independent contribution of quantitative image markers …