cancer computational pathology computer vision deep learning digital pathology grand-challenge.org histopathology life sciences machine learning medical image computing medical imaging
This dataset contains the training data for the CHIMERA - Combining HIstology, Medical imaging (radiology) and molEcular data for medical pRognosis and diAgnosis challenge. The CHIMERA Challenge aims to advance precision medicine in cancer care by addressing the critical need for multimodal data integration. Despite significant progress in AI, integrating transcriptomics, pathology, and radiology across clinical departments remains a complex challenge. Clinicians are faced with large, heterogeneous datasets that are difficult to analyze effectively. AI has the potential to unify multimodal data, but several technical barriers remain, such as defining appropriate fusion stages and handling missing modalities.
As required
CC BY-NC-SA 4.0
https://chimera.grand-challenge.org/
Radboud University Medical Center
See all datasets managed by Radboud University Medical Center.
CHIMERA was accessed on DATE
from https://registry.opendata.aws/chimera.
arn:aws:s3:::chimera-challenge
us-west-2
aws s3 ls --no-sign-request s3://chimera-challenge/