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RequestUpdated on 12 January 2026

Multi-centric validation of AI models for prostate cancer screening

Data strategist at BBMRI-ERIC EOSC Node

Vienna, Austria

About

Overview

The BBMRI-ERIC EOSC Node invites organizations to join the Multi-Centric Validation of AI Models for Prostate Cancer Screening (MCVAL). MCVAL aims to validate prostate cancer screening AI models across diverse datasets and secure computing environments.

Who Can Contribute?

Hospitals and pathology departments; Biobanks and research infrastructures; HPC/Cloud providers capable of secure data processing; AI developers in digital pathology.

A) Sensitive Health Data

Contribute WSIs and metadata meeting specifications: prostate biopsy WSIs, OpenSlide-readable formats, slide-level labels, optional spatial annotations, GDPR-compliant data handling, informed consent.

B) Secure Computational Resources

Provide infrastructure for sensitive data: ISO 27001-class security, SPE principles, GPU-enabled HPC/cloud, container orchestration.

C) AI Models for Prostate Cancer Screening

Contribute AI models for WSI analysis, including slide-level or patch-level classifiers, weakly supervised or foundation models, container-deployable formats.

Benefits of Participation

Advance early detection; increase visibility within EOSC; strengthen reproducibility; contribute to secure European health-data research.

Organisation

BBMRI-ERIC EOSC Node

Thematic EOSC Node

Austria

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