First Header Logo Second Header Logo

Oguz Akbilgic PhD

TitleAssociate Professor
InstitutionWake Forest School of Medicine
DepartmentInternal Medicine, Cardiovascular Medicine
vCardDownload vCard

    Collapse Biography 
    Collapse education and training
    University of Calgary, CalgaryPostdoc04/2015AI/Engineering
    University of Tennessee, Knoxville, TNPostdoc07/2013AI/Statistics
    Mimar Sinan University, IstanbulPhD12/2022Machine Learning/Statistics
    Istanbul University, IstanbulPhD06/2011Machine Learning/Business Administration
    Mimar Sinan University, IstanbulMS02/2005Operations Research/Statistics
    Istanbul University, IstanbulBS07/2001Mathematics

    Collapse Overview 
    Collapse overview
    Oguz Akbilgic, DBA, PhD is a biomedical informaticist, innovator and entrepreneur with training and expertise in machine learning, statistical modeling and business administration. His research focus is on the development of AI models for detection, risk prediction, and prognostic assessment of cardiovascular diseases including but not limited to heart failure, sudden cardiac death, cardiomyopathies, valvular disease, arrhythmias. He also has active research projects on detection and risk prediction neurodegenerative diseases (e.g. Parkinson's Disease, Alzheimers Disease, Dementia) and adverse maternal events.

    His research lab includes seven PHD or MD level members with expertise in AI, machine learning, cardiology, computational biology, computer science and mobile app development.

    He has published and presented over 100 research projects including two book chapters (link for Google Scholar Profile)

    Dr. Akbilgic is the PI or MPI on several active projects funded by NIH, Michael J Fox Foundation, and Atrium Health.

    R01-HL169451 ECG-AI Based Prediction and Phenotyping of Heart Failure with Preserved Ejection Fraction (PI Akbilgic)
    R01-CA261834 Early Identification of Childhood Cancer Survivors at High Risk for Late Onset Cardiomyopathy: An Artificial Intelligence Approach utilizing Electrocardiography (MPIs Akbilgic & Hudson)
    R21-HL167126 Deep learning of awake and sleep electrocardiography to identify atrial fibrillation risk in sleep apnea (MPIs Younghoon, Akbilgic, Azarbarzin)
    ECG-AI Based Risk Prediction of Parkinson's Disease (funded by Michael J Fox Foundation)

    Collapse Featured Content 
    Collapse Twitter
    Same Department Expand Description