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Emory researchers receive $2.7 million to study use of data to predict atrial fibrillation
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The National Heart, Lung and Blood Institute has awarded a $2.7 million grant to Emory University and Emory Healthcare researchers to study the use of data strategies to detect and predict atrial fibrillation in post-stroke patients.

Xiao Hu, PhD, Asa Griggs Candler Professor at Emory’s Nell Hodgson Woodruff School of Nursing, and Fadi Nahab, MD, associate professor in the Department of Neurology and Pediatrics at the Emory School of Medicine and Stroke Quality Director at Emory Healthcare, will lead the four-year R01 grant. Hu is also associate director of the Center for Data Science in the School of Nursing.

Atrial fibrillation is the most common form of arrhythmia (irregular heartbeat), affecting 33.5 million people globally. Atrial fibrillation is associated with significant morbidity and mortality, including 20% of all strokes, 33% of hospitalizations related to cardiac arrhythmias, and a two-fold increase in the risk of death.

To diagnose the condition early and initiate stroke prevention interventions, the research team will develop an integrated data and algorithm strategy to validate the power of deep neural networks — a class of machine learning algorithms that aims to mimic the information processing of the brain — in using photoplethysmography (PPG) from wearable devices to detect atrial fibrillation. PPG utilizes infrared/green light to measure volume variations of blood circulation and provides valuable information about the cardiovascular system.

In collaboration with Cynthia Rudin, PhD, a computer scientist from Duke University, the team will develop interpretable survival models to analyze electronic health record data to predict atrial fibrillation risk for stroke survivors and provide decision support to select the most effective approaches to monitor the condition.

Other team members working on the study include Corey Williams, lead study coordinator; Del Bold, software engineer; Cheng Ding, a PhD student from Georgia Tech/Emory BME program; and Cynthia Rudin from the Duke University Department of Computer Science. Also participating are Emory colleagues Wonshik Chee and Melinda Higgins (Emory School of Nursing), Rishi Kamaleswaran (Emory Department of Computer Science), and Stacey Westerman and Michael El Chami (Emory School of Medicine/Emory Heart & Vascular Center).

This research is supported by the National Heart, Lung and Blood Institute of the National Institutes of Health under Award Number R01HL166233 and is registered as DELTA (Detecting and Predicting Atrial Fibrillation in Post-Stroke Patients) on The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. 

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