Truveta Data
Images
Largest collection of medical images integrated with EHR data
De-identified medical images are often difficult to find and detached from clinical context
Truveta Data includes millions of images integrated with patient medical records, enabling more complete research.
studies and growing
CTs
MRIs
mammograms
ultrasounds
Explore images across modalities and therapeutic areas
Truveta provides pixel data and imaging metadata including MRI, CT, X-ray, ultrasound, mammogram, PET, and nuclear medicine, searchable by modality and protocol.
Lung CT
Lung CT metadata
Truveta provides pixel data and imaging metadata including MRI, CT, X-ray, ultrasound, mammogram, PET, and nuclear medicine, searchable by modality and protocol.
Lung CT metadata
Complete metadata is included with each image, including size, dimensions, bit depth, modality, and equipment settings.
Study medical images integrated with longitudinal EHR data
Images are part of Truveta Data, which includes complete EHR data for more than 100 million patients, linked with claims, SDOH, and mortality data.
Data are representative of inpatient and outpatient care across the US, and are updated daily from members, cleaned with clinical expert-led AI, and de-identified with industry-leading privacy and security technology.
Accelerate research with integrated analytical tools
Truveta Studio enables researchers to preview images and easily annotate using built-in tools.
Research using echocardiogaphy doppler for machine learning
De-identified images can be analyzed in notebooks in Truveta Studio and exported for studying imaging-based outcomes and observations, AI/machine learning model development, or inclusion in publications.
Learn more about the depth of Truveta Data
Regulatory-grade EHR data
Truveta offers complete, timely, and clean EHR data linked with SDOH, mortality, and claims data for more than 100M patients representing the full diversity of the US.
More than 5 billion clinical notes
Truveta uses clinical expert-led AI to clean and structure data from notes at scale, enabling researchers to understand patients’ complete clinical context and answer novel research questions.