Artifical Intelligence in Cardiology
Overview:
Cardiovascular disease (CVD) has consistently been the leading cause of death worldwide. Early and accurate diagnosis is the key in improving cardiac morbidity and reducing cardiac mortality. Artificial Intelligence (AI) methods and technologies promise simultaneous analysis of large datasets in a way human brain cannot process to assist clinicians in timely diagnosis and therapeutics. This talk will focus on AI applications in cardiology, opportunities, and challenges.
Speaker:
Oguz Akbilgic, PhD, is an associate professor in the Department of Health Informatics and Data Science at Loyola University Chicago's Parkinson School of Health Sciences and Public Health. He earned his doctorate degree in Quantitative Methods with a focus on Artificial Neural Networks from Istanbul University in 2011. He completed his postdoctoral studies on machine learning at University of Tennessee, Knoxville, and University of Calgary between 2012-2015. He worked at the Center for Biomedical Informatics at the University of Tennessee Health Sciences Center, Memphis, TN, from 2015 to 2019 until joining Loyola. His lab focuses on method development in statistics and machine learning as well as their applications in health outcomes. His lab has a specific focus in artificial intelligence applications in cardiac arrhythmia classification and cardiovascular disease risk prediction. He has published about 100 scientific work including about 50 peer reviewed articles and a book chapter. He is currently a PI of a multicenter study to implement Artificial Intelligence on ECG data for Early Diagnosis of Parkinson’s Disease funded by Michael J Fox Foundation.
Watch previous presentations and to find more information about future seminars.
Originally recorded on Wednesday, February 24, 2021, as part of CHOIR's
Overview:
Cardiovascular disease (CVD) has consistently been the leading cause of death worldwide. Early and accurate diagnosis is the key in improving cardiac morbidity and reducing cardiac mortality. Artificial Intelligence (AI) methods and technologies promise simultaneous analysis of large datasets in a way human brain cannot process to assist clinicians in timely diagnosis and therapeutics. This talk will focus on AI applications in cardiology, opportunities, and challenges.
Speaker:
Oguz Akbilgic, PhD, is an associate professor in the Department of Health Informatics and Data Science at Loyola University Chicago's Parkinson School of Health Sciences and Public Health. He earned his doctorate degree in Quantitative Methods with a focus on Artificial Neural Networks from Istanbul University in 2011. He completed his postdoctoral studies on machine learning at University of Tennessee, Knoxville, and University of Calgary between 2012-2015. He worked at the Center for Biomedical Informatics at the University of Tennessee Health Sciences Center, Memphis, TN, from 2015 to 2019 until joining Loyola. His lab focuses on method development in statistics and machine learning as well as their applications in health outcomes. His lab has a specific focus in artificial intelligence applications in cardiac arrhythmia classification and cardiovascular disease risk prediction. He has published about 100 scientific work including about 50 peer reviewed articles and a book chapter. He is currently a PI of a multicenter study to implement Artificial Intelligence on ECG data for Early Diagnosis of Parkinson’s Disease funded by Michael J Fox Foundation.
Watch previous presentations and to find more information about future seminars.