Real-world data created by natural human activity. Select a domain below to learn more.
Discrete, machine-readable fields such as EHR data, claims, codes, medications, procedures, vitals, and genomics.
Free-text clinical notes, chat and portal messages, documentation, and other narrative descriptions of patient care such as doctor-patient audio conversations.
Radiology, radiology, pathology, WSI, and other medical imaging, along with associated metadata, reports, and annotations.
PDF reports, scans, faxed materials, and other forms of documentation that sit in EMR systems and left underutilized.
The ability for a model to reason through data requires a fundamentally different approach to data curation than what exists for traditional RWE research. Our methods ensure compliance while preserving the rich context that is needed to AI training.
This means doing the hard work of gathering data from a heterogeneous set of sources, standardizing them, pooling them, linking them, all while ensuring a clear view whether we are talking about a single patient encounter or a whole population of patient journeys.
We create datasets for your specific training purpose. We analyze what is needed, and construct datasets that balance the realities of real world data with research robustness to responsibly train unbiased models.
With access to hundreds of millions of patients across modalities, Protege's DataLab research team designs and builds realistic healthcare benchmarks on top of anonymized and de-identified real-world patient data that still retains context.
Protege ingests multiple modalities from trusted data partners to create fully packaged patient encounters to match your specific model training or evaluation needs.
Explore our healthcare data and expertise
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This partnership introduces one of the most scalable and lab-centric datasets on the market, enabling AI developers to access rich, de-identified laboratory data across the…
Summary Protege offers multimodal data aggregation and standardization with AI training/evaluation curation aligned to foundation model builders, delivered with enterprise-grade compliance and repeatable, deal-driven programs.…
Summary Healthcare Data for Real World Use Cases: A leading healthcare AI company partnered with Protege to connect its patient-level data to Loopback Health’s EHR…
Summary Millions of Images in 30 Days: A leading AI model builder sourced millions of de-identified imaging studies in a month of contract execution via…
Robust healthcare AI evaluations require benchmark-specific real world data that does not overlap with training data, while also reflecting the full multimodal patient journey. Current…
Summary Data Licensing Revenue Unlocked: Gradient Health, a leading provider of medical imaging studies, partnered with Protege to license de-identified, HIPAA‑compliant data at scale, unlocking…
