NextGen
Hidden Data Products
Discover previously inaccessible datasets across institutions through our decentralized search.
Federated medical-data platform
Build ML models on institutional medical data at source.
Accelerate research, advance treatment, change lives for the better.
Federated
Imaging Segmentation Suite
v1.2.0Automated segmentation of medical imaging with federated model training.
imagingsegmentation
HUS
Apache-2.0
Federated
Cohort Builder
v3.0.4Assemble and refine patient cohorts from harmonised metadata.
cohortanalyticsselection
KI
MIT
Library
DCAT-AP Validator
v0.9.2Check dataset metadata against the DCAT-AP 3 profile before publishing.
dcat-apmetadatavalidation
UMCU
EUPL-1.2
Library
MMIO Toolkit
v1.5.0Parse, transform and export machine-readable metadata input objects.
mmioetlmetadata
UvA
Apache-2.0
Utility
Consent Manager
v2.1.3Track and enforce data-use agreements and access conditions.
consentaccessgovernance
TUM
GPL-3.0
Utility
Insight Charts
v0.4.0Generate shareable visualisations from federated aggregate results.
chartsvisualization
HUS
MIT
Full Compliance
Access sensitive data while maintaining full compliance with patient privacy laws.
Better Models
Train ML models on diverse, multi-institutional data without extraction or duplication.
Real-World Impact
Cardiovascular Research Network
A multi-institution team used NextGen to build predictive models across hospitals without transferring sensitive patient data. Their federated learning approach incorporated genetic markers, imaging data, and clinical records while maintaining complete regulatory compliance.
Result: accelerated research timeline while ensuring data sovereignty and regulatory compliance.