Trained on the Truveta Language Model and Truveta Data, the most complete and representative EHR data, Tru enables researchers to accelerate their research in Truveta Studio using simple, natural language
Truveta Tru enables researchers to accelerate their medical research
Truveta Tru enables researchers to quickly develop hypotheses
Tru is the latest AI innovation from Truveta to help advance its mission of Saving Lives with Data. Truveta Data is powered by the Truveta Language Model (TLM), the first large-language, multi-modal model trained on the most complete, clean, and representative electronic health record (EHR) data and has achieved above 90% precision across clinical domains. TLM cleans billions of EHR data points, including concepts extracted from clinical notes, to accelerate adoption of new therapies, improve clinical trials, and enhance patient care. And today, Tru can assist the researcher in speeding time to insight.
"Truveta Data enables AI to unlock insights that can improve care for everyone - with billions of data points cleaned daily for research on any drug, disease, or device,” said Jay Nanduri, chief technology officer and co-founder, Truveta. "With Tru, researchers can use natural language questions to speed their scientifically rigorous research in Truveta Studio. We envision expanding this technology with significant capabilities in the coming months as we continue to invest deeply in AI to unravel the health mysteries that will help us realize our mission of Saving Lives with Data.”
Tru enables researchers to:
- Accelerate research. Quickly identify code sets, build and visualize patient populations quickly, and build and modify population definitions. For a researcher looking to study GLP-1 RA medications (e.g., semaglutide, tirzepatide, etc.), Tru can build the logic to find all patients prescribed or dispensed these medications and then can immediately show trends of the different medications over time to better understand prescribing patterns.
- Develop hypotheses. Discover trends through iterative prompts and data visualizations. For example, a researcher monitoring hospitalizations associated with viral gastroenteritis could simply ask Tru using natural language to create a time series visualization of viral gastroenteritis diagnoses by month-year. To quickly analyze the distribution of myocardial infarction across demographic groups, simply prompt Tru to create a heatmap of myocardial infarction cases by race and gender.
- Transparent assistance. Access source information and underlying code sets behind responses. Unlike other generative AI tools, Tru provides transparency into its process, sources, and underlying code so that researchers can be confident and informed about the responses it generates and provide feedback to further improve the model.
To learn more about Tru and the Truveta Language Model, visit Truveta.com.
About Truveta
Truveta is a collective of US health systems with a mission of Saving Lives with Data. Truveta delivers the most complete, clean, and timely regulatory-grade EHR data for scientifically rigorous research. Truveta is trusted by leading life science, public health, healthcare, and academic organizations to accelerate adoption of new therapies, improve clinical trials, and enhance patient care.
Truveta membership includes Providence, Advocate Health, Trinity Health, Tenet Healthcare, Northwell Health, AdventHealth, Baptist Health of Northeast Florida, Baylor Scott & White Health, Bon Secours Mercy Health, CommonSpirit Health, Hawaii Pacific Health, HealthPartners, Henry Ford Health System, HonorHealth, Inova, Lehigh Valley Health Network, MedStar Health, Memorial Hermann Health System, MetroHealth, Novant Health, Ochsner Health, Premier Health, Saint Luke's Health System, Sanford Health, Sentara Healthcare, Texas Health Resources, TriHealth, UnityPoint Health, Virtua Health, and WellSpan Health.
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Truveta Tru enables researchers to accelerate their medical research
Truveta Tru enables researchers to quickly develop hypotheses
CONTACT: Alisha Schilter
Truveta
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