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Department of Biomedical Informatics Launches to Advance Patient Care Using Data-Driven Discovery

Connecting basic science and medicine with clinical and translational scientists, the University of Colorado School of Medicine is introducing the Department of Biomedical Informatics (DBMI) to enhance clinical care through integrated computational technology, laboratory investigations, and artificial intelligence (AI).


Author Rachel Wittel | Publish Date July 06, 2022
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Department of Biomedical Informatics In the News

Patient-Centered Outcomes Research Institute

Develop Novel Methods to Identify and Characterize Family Relationships from Electronic Health Data

news outletPatient-Centered Outcomes Research Institute
Publish DateNovember 21, 2022

Understanding household and family memberships has always been important in distinguishing the influence of shared genetics and environments on clinical risks and patient outcomes. Electronic health records (EHR) often include vast information about individuals that, if linked with that of their household or family members, could provide rich and detailed environmental and family history information to support scientific discovery, and patient-centered outcomes research.

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Science Direct

Artificial intelligence in echocardiography to diagnose congenital heart disease and fetal echocardiography

news outletScience Direct
Publish DateNovember 09, 2022

Echocardiography is the primary tool in pediatric cardiology for diagnosing and managing congenital heart disease (CHD). Accurate and reliable echocardiographic assessment is critical in clinical decision making. Artificial intelligence (AI), in particular deep learning, has the potential to reduce labor and provide automated assessment of CHD. 

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Nature Communications

Systematic tissue annotations of genomics samples by modeling unstructured metadata

news outletNature Communications
Publish DateNovember 08, 2022

There are currently >1.3 million human –omics samples that are publicly available. This valuable resource remains acutely underused because discovering particular samples from this ever-growing data collection remains a significant challenge. The major impediment is that sample attributes are routinely described using varied terminologies written in unstructured natural language.

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National Institutes of Health (NIH)

Advancing American Indian and Alaska Native Health Through Research, Training, and Engagement

news outletNational Institutes of Health (NIH)
Publish DateNovember 02, 2022

American Indian and Alaska Native (AI/AN) populations have long experienced health disparities such as higher rates of diabetes, certain cancers, and mental health conditions than those of other Americans. One contributing factor in these disparities is underrepresentation of AI/AN populations in biomedical science—as study participants, researchers, and health professionals.

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