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CHIMERA

cancer computational pathology computer vision deep learning digital pathology grand-challenge.org histopathology life sciences machine learning medical image computing medical imaging

Description

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.

Update Frequency

As required

License

CC BY-NC-SA 4.0

Documentation

https://chimera.grand-challenge.org/

Managed By

Radboud University Medical Center

See all datasets managed by Radboud University Medical Center.

Contact

nadieh.khalili@radboudumc.nl

How to Cite

CHIMERA was accessed on DATE from https://registry.opendata.aws/chimera.

Usage Examples

Tools & Applications

Resources on AWS

  • Description
    Task 1 includes paired MRI and H&E-stained whole slide images with corresponding clinical data and biochemical recurrence information. Task 2 includes H&E slides, clinical data, and recurrence status in bladder cancer. Task 3 includes H&E slides, RNA-seq clinical data, and recurrence status in bladder cancer.
    Resource type
    S3 Bucket
    Amazon Resource Name (ARN)
    arn:aws:s3:::chimera-challenge
    AWS Region
    us-west-2
    AWS CLI Access (No AWS account required)
    aws s3 ls --no-sign-request s3://chimera-challenge/

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