EHR Selection

Machine-Learning Intervention Leads to Safer Cardiac Catheterization

February 8, 2023 - As reported in the Clinical Journal of the American Society of Nephrology, a randomized trial conducted by Vanderbilt University Medical Center (VUMC), the Dartmouth Geisel School of Medicine, and the Larner College of Medicine at the University of Vermont found that a machine-learning intervention provided a higher level of safety during cardiac...

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New AI System Assists Medication Selection for Type 2 Diabetics

by Mark Melchionna

Using EHR data from various healthcare institutions, Hitachi, University of Utah Health, and Regenstrief Institute collaborated to create an artificial intelligence (AI) method to enhance type 2...

AI Method Helps Further Outcomes-Based Research for Cardiovascular Disease

by Mark Melchionna

Researchers used University of Utah and Primary Children’s Hospital EHRs to create a Poisson Binomial-based Comorbidity (PBC) method that can help shine a light on the impacts of comorbid...

Natural Language Processing Helps Assess COVID-19 Complications

by Erin McNemar, MPA

To understand the relationship between pre-existing conditions and complications of COVID-19 infection, researchers are using natural language processing (NLP) to sift through unstructured EHR...

EHR Data Boosts Machine Learning Algorithms for Chronic Disease

by Erin McNemar, MPA

By using machine learning algorithms, researchers examined if creating a large-scale electronic health record (EHR) data-based lung cancer cohort could be effective in studying a patient’s...

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