Department of Biomedical Informatics Archive — Page 16 of 26

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March 15, 2021

Artificial intelligence calculates suicide attempt risk at VUMC

A machine learning algorithm that predicts suicide attempt recently underwent a prospective trial at the institution where it was developed, Vanderbilt University Medical Center.

March 11, 2021

Genotype looms large in risk for post-op arrhythmia

Postoperative atrial fibrillation (PoAF), a form of arrhythmia, complicates 20-40% of cardiac surgical procedures and 10–20% of non-cardiac thoracic operations, cropping up two to four days after surgery to pose risk of stroke, heart attack, mortality, longer hospital stays and greater cost.

Logo reading “All of Us Research Program” in white and light blue on a dark navy background.
March 4, 2021

COVID-19 survey data added to All of Us platform

In December 2020, the federal government’s massive precision medicine research initiative, All of Us (AoU), made available to qualified researchers initial results from its ongoing COVID-19 Participant Experience (COPE) Survey, as well as physical activity and heart rate data collected from Fitbit devices worn by AoU participants.

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February 25, 2021

Epic founder Faulkner highlights DBMI online seminar

The CEO and founder of one of the world’s largest electronic health record (EHR) vendors, Judith Faulkner of Epic Systems Corp., spoke about her company and answered questions recently at the Department of Biomedical Informatics weekly online seminar.

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February 11, 2021

Grant supports speedy sorting of health records by phenotype

Wei-Qi Wei, MD, PhD, assistant professor of Biomedical Informatics and scientific director of the Precision Phenotyping Core at the Center for Precision Medicine, has been awarded a four-year, $1.7 million grant from the National Institutes of Health (grant GM139891) to continue

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February 11, 2021

Study will delve into EHR for signs of suicidality

Retrieval of clearer, more complete information from the EHR could go a long way toward improving predictive models of who will next be at risk of suicide, thereby improving care for patients with suicidal thoughts and behaviors.