Evals & Benchmarks

Data & Expertise for Healthcare Evaluation

High Quality Evaluations for Healthcare AI. Evaluations built on real-world data to simulate real world scenarios.

Healthcare Evaluations

Healthcare EvaluationsProtege provides high quality evaluations for model builders to determine where their models are succeeding, identify failure points, and provide evidence for model quality.

Why are Healthcare Benchmarks so difficult?

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Our Evaluation Approach

Real-world by design

Evaluations that use real clinical and administrative data to test decisions, workflows, and edge cases that healthcare AI actually encounters.

Protected held-out testing

Test cases remain private and separate from model development with contamination controls, allowing you to test your model against never before seen data.

Standardized and repeatable

Versioned tasks, ground truth, and scoring make results comparable across model releases and repeatable as products improve.

Actionable failure analysis

Results reveal failure patterns, affected populations, and important limitations so teams know where they are succeeding and where they can improve.

Why Protege

Healthcare data at scale

Protege provides access to rights-cleared, real-world healthcare data across institutions, populations, and use cases

Linked, multimodal context

We connect structured EHR data with notes, imaging, pathology, claims, and outcomes to represent the full context behind healthcare decisions

DataLab research expertise

Protege researchers and domain experts translate healthcare questions into rigorous tasks, credible ground truth, and defensible evaluation methods

Independent, governed execution

Protege maintains the proper data rights, de-identification, secure access, test-set integrity, model execution, and grading independent of the model builder

Faqs

Healthcare AI is actively being deployed at the point of care across the United States. AI builders and buyers need credible evidence that these systems work across real patients and populations rather than just on development data.

Protege designs and runs real-world evaluations that reveal where healthcare AI performs well and where it fails. We have already developed evaluations spanning diagnostic journeys, pathology, dermatology, multimodal oncology, and healthcare-administration workflows, with more to come.

Protege combines rights-cleared healthcare data, linked multimodal context, and research expertise from our DataLab team of researchers. We use private held-out test cases, independent execution, and rigorous grading to turn model performance into actionable failure analysis.

Protege works with frontier AI labs, healthcare AI application builders, healthcare organizations, data partners, and clinical experts. Together, we build evaluations around consequential model claims and workflows found in the real-world.

Protege uses de-identified, real-world healthcare data — including structured EHR data, clinical notes, claims, medical documents, pathology slides, imaging, genomics, treatments, and outcomes. The exact data depends on the application and question being evaluated.

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Contact for Data Access & Benchmark Expertise

Data & Expertise for Healthcare Evaluation

Healthcare Evaluations

Why are Healthcare Benchmarks so difficult?