oguz akbilgic

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Associate Professor

Wake Forest School of Medicine

United States

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Recent Grants

Grant: Close

Applying Artificial Intelligence for Early Identification of Parkinson’s Disease

Open Date: 2019-10-01

Close Date: 2021-11-01

Grant: Close

Socioeconomic Background of Pediatric Surgical Disparities

Open Date: 2018-10-01

Close Date: 2019-09-01

Articles (18)

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2024

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2021

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2021

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2020

Collaborators (3)

Ibrahim Karabayir

Assistant Professor

Wake Forest Baptist Medical Center

UNITED STATES

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Lokesh Chinthala

University of Tennessee Health Science Center

UNITED STATES

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Liam Butler

Wake Forest University

UNITED STATES

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oguz akbilgic

Research Interests

Explore related searches

Contact this professor

Recent Grants

Articles (18)

Outcomes of Ultrafiltration in community-based hospitals.

Feasibility of remote monitoring for fatal coronary heart disease using Apple Watch ECGs.

AI-based preeclampsia detection and prediction with electrocardiogram data.

Development and validation of an electrocardiographic artificial intelligence model for detection of peripartum cardiomyopathy

Principles of Artificial Intellgence for Medicine

A generalizable electrocardiogram-based artificial intelligence model for 10-year heart failure risk prediction.

Pretreatment identification of 90-day readmission among heart failure patients receiving aquapheresis treatment.

Incidence, mortality and disability-adjusted life years of acute myocardial infarction in Kazakhstan: data from unified national electronic healthcare system 2014-2019.

AI-Enabled ECG for Paroxysmal Atrial Fibrillation Detection: One Step to Closer to the Finish Line.

Externally validated deep learning model to identify prodromal Parkinson's disease from electrocardiogram.

Image and structured data analysis for prognostication of health outcomes in patients presenting to the ED during the COVID-19 pandemic

ECG-AI: electrocardiographic artificial intelligence model for prediction of heart failure

The role of frailty index in predicting readmission risk following total joint replacement using light gradient boosting machines

Artificial Intelligence–Assisted Prediction of Late-Onset Cardiomyopathy Among Childhood Cancer Survivors

Application of machine learning to the prediction of postoperative sepsis after appendectomy

A Novel Learning Algorithm to Optimize Deep Neural Networks: Evolved Gradient Direction Optimizer (EVGO)

Gradient boosting for Parkinson’s disease diagnosis from voice recordings

Comparative analysis between convolutional neural network learned and engineered features: A case study on cardiac arrhythmia detection

Collaborators (3)

Ibrahim Karabayir

Lokesh Chinthala

Liam Butler

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