EvidenceOS CCR Lab — Collaborative Clinical Research Laboratory platform. Code, protocols, and public outputs from the CCR Lab research program.
Active development. CCR Lab is EvidenceOS's primary academic research production unit.
publications/— Pre-prints, accepted manuscripts, and supplementary materials (open-access)protocols/— Pre-registered study protocols (OSF + PROSPERO links)datasets/— Synthetic datasets and de-identified summary statistics from CCR Lab studiestools/— Open research tools developed by the CCR Lab team
The CCR Lab generates the peer-reviewed evidence base that validates EvidenceOS's clinical AI claims. The Lab's publication pipeline (80+ papers tracked) spans:
- Living systematic reviews of TBI prediction models
- CONSORT-Outcomes analysis of adult TBI RCTs
- AI-assisted evidence extraction validation
- Multiverse analysis of TBI biomarker prediction
- Delphi consensus panels for clinical AI evaluation standards
CCR Lab publications are tracked against the Finnish OKM (Ministry of Education and Culture) JUFO tier classification system. Publications in JUFO-tier 2/3 journals contribute to the €4.45M OKM revenue target.
CCR Lab is a joint initiative between EvidenceOS and the University of Turku (UTU) Department of Neurosurgery. Co-investigators include Drs. Harri Merisaari and Jussi Posti.
External co-authorship opportunities available through RAIGH Academy and the Ambassador Network. Reach out via research@evidenceos.com.
- Publications: open-access per journal policy
- Tools: MIT
- Protocols: CC-BY-4.0
CCR Lab Research Team — research@evidenceos.com
ccrl-network— CCR Lab Network (multi-institution)evidence-commons— Canonical evidence libraryraigh-academy— Research training programtbi-prediction-models— TBI prediction model systematic review