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Oguz Akbilgic PhD

TitleAssociate Professor
InstitutionWake Forest School of Medicine
DepartmentInternal Medicine, Cardiovascular Medicine
Address
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    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.

    Collapse Research 
    Collapse research activities and funding
    R01CA261834     (AKBILGIC, OGUZ)Apr 15, 2022 - Mar 31, 2026
    NIH
    Early Identification of Childhood Cancer Survivors at High Risk for Late Onset Cardiomyopathy: An Artificial Intelligence Approach utilizing Electrocardiography
    Role: Principal Investigator
    R21HL167126     (KWON, YOUNGHOON)Jan 15, 2023 - Dec 31, 2024
    NIH
    Deep learning of awake and sleep electrocardiography to identify atrial fibrillation risk in sleep apnea
    Role: Co-Investigator
    R01HL169451     (AKBILGIC, OGUZ)Sep 1, 2023 - May 31, 2027
    NIH
    ECG-AI Based Prediction and Phenotyping of Heart Failure with Preserved Ejection Fraction
    Role: Principal Investigator

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    Collapse Bibliographic 
    Collapse selected publications
    Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.
    Newest   |   Oldest   |   Most Cited   |   Most Discussed   |   Timeline   |   Field Summary   |   Plain Text
    PMC Citations indicate the number of times the publication was cited by articles in PubMed Central, and the Altmetric score represents citations in news articles and social media. (Note that publications are often cited in additional ways that are not shown here.) Fields are based on how the National Library of Medicine (NLM) classifies the publication's journal and might not represent the specific topic of the publication. Translation tags are based on the publication type and the MeSH terms NLM assigns to the publication. Some publications (especially newer ones and publications not in PubMed) might not yet be assigned Field or Translation tags.) Click a Field or Translation tag to filter the publications.
    1. Chinta VR, Theella NP, Raja JM, Rawal A, Bath A, Jones D, Ibrahim A, Asbeutah AAA, Adeboye AA, Akbilgic O, Khouzam RN, Stamper JJ, Jefferies JL. Outcomes of Ultrafiltration in community-based hospitals. Curr Probl Cardiol. 2024 Oct; 49(10):102716. PMID: 38909929.
      Citations:    
    2. Akbilgic O. Principles of Artificial Intellgence for Medicine. J Am Heart Assoc. 2024 Jun 18; 13(12):e035815. PMID: 38879454.
      Citations:    
    3. Butler L, Ivanov A, Celik T, Karabayir I, Chinthala L, Hudson MM, Ness KK, Mulrooney DA, Dixon SB, Tootooni MS, Doerr AJ, Jaeger BC, Davis RL, McManus DD, Herrington D, Akbilgic O. Feasibility of remote monitoring for fatal coronary heart disease using Apple Watch ECGs. Cardiovasc Digit Health J. 2024 Jun; 5(3):115-121. PMID: 38989042.
      Citations:    
    4. Butler L, Gunturkun F, Chinthala L, Karabayir I, Tootooni MS, Bakir-Batu B, Celik T, Akbilgic O, Davis RL. AI-based preeclampsia detection and prediction with electrocardiogram data. Front Cardiovasc Med. 2024; 11:1360238. PMID: 38500752.
      Citations:    
    5. Karabayir I, Wilkie G, Celik T, Butler L, Chinthala L, Ivanov A, Moore Simas TA, Davis RL, Akbilgic O. Development and validation of an electrocardiographic artificial intelligence model for detection of peripartum cardiomyopathy. Am J Obstet Gynecol MFM. 2024 Apr; 6(4):101337. PMID: 38447673.
      Citations:    
    6. Alkhatib D, Karabayir I, Pour-Ghaz I, Khan S, Hart L, Cease M, Khouzam RN, Jefferies JL, Akbilgic O. Pretreatment identification of 90-day readmission among heart failure patients receiving aquapheresis treatment. Curr Probl Cardiol. 2024 Feb; 49(2):102207. PMID: 37967805.
      Citations:    
    7. Willis KA, Silverberg M, Martin I, Abdelgawad A, Karabayir I, Halloran BA, Myers ED, Desai JP, White CT, Lal CV, Ambalavanan N, Peters BM, Jain VG, Akbilgic O, Tipton L, Jilling T, Cormier SA, Pierre JF, Talati AJ. The fungal intestinal microbiota predict the development of bronchopulmonary dysplasia in very low birthweight newborns. medRxiv. 2023 Nov 10. PMID: 37398134.
      Citations:    
    8. Butler L, Karabayir I, Kitzman DW, Alonso A, Tison GH, Chen LY, Chang PP, Clifford G, Soliman EZ, Akbilgic O. A generalizable electrocardiogram-based artificial intelligence model for 10-year heart failure risk prediction. Cardiovasc Digit Health J. 2023 Dec; 4(6):183-190. PMID: 38222101.
      Citations:    
    9. Zhakhina G, Gaipov A, Salustri A, Gusmanov A, Sakko Y, Yerdessov S, Bekbossynova M, Abbay A, Sarria-Santamera A, Akbilgic O. Incidence, mortality and disability-adjusted life years of acute myocardial infarction in Kazakhstan: data from unified national electronic healthcare system 2014-2019. Front Cardiovasc Med. 2023; 10:1127320. PMID: 37600059.
      Citations:    
    10. Karabayir I, Gunturkun F, Butler L, Goldman SM, Kamaleswaran R, Davis RL, Colletta K, Chinthala L, Jefferies JL, Bobay K, Ross GW, Petrovitch H, Masaki K, Tanner CM, Akbilgic O. Externally validated deep learning model to identify prodromal Parkinson's disease from electrocardiogram. Sci Rep. 2023 Jul 29; 13(1):12290. PMID: 37516770.
      Citations:    
    11. Kalscheur MM, Akbilgic O. AI-Enabled ECG for Paroxysmal Atrial Fibrillation Detection: One Step to Closer to the Finish Line. JACC Clin Electrophysiol. 2023 Aug; 9(8 Pt 3):1783-1785. PMID: 37498242.
      Citations:    
    12. Bath A, Akbilgic O, Wilbanks D, Patel J, Wallen M, Haji S, Das A, Alexander J, Pour-Ghaz I, Alkhatib D, Huang Y, Lontok E, Jefferies J. Barth Syndrome: Psychosocial Impact and Quality of Life Assessment. J Cardiovasc Dev Dis. 2022 Dec 09; 9(12). PMID: 36547445.
      Citations:    
    13. Suero-Abreu GA, Hamid A, Akbilgic O, Brown SA. Trends in cardiology and oncology artificial intelligence publications. Am Heart J Plus. 2022 May; 17:100162. PMID: 38559882.
      Citations:    
    14. Martinez DS, Noseworthy PA, Akbilgic O, Herrmann J, Ruddy KJ, Hamid A, Maddula R, Singh A, Davis R, Gunturkun F, Jefferies JL, Brown SA. Artificial intelligence opportunities in cardio-oncology: Overview with spotlight on electrocardiography. Am Heart J Plus. 2022 Mar; 15. PMID: 35721662.
      Citations:    
    15. Karabayir I, Butler L, Goldman SM, Kamaleswaran R, Gunturkun F, Davis RL, Ross GW, Petrovitch H, Masaki K, Tanner CM, Tsivgoulis G, Alexandrov AV, Chinthala LK, Akbilgic O. Predicting Parkinson's Disease and Its Pathology via Simple Clinical Variables. J Parkinsons Dis. 2022; 12(1):341-351. PMID: 34602502.
      Citations:    
    16. Butler L, Karabayir I, Samie Tootooni M, Afshar M, Goldberg A, Akbilgic O. Image and structured data analysis for prognostication of health outcomes in patients presenting to the ED during the COVID-19 pandemic. Int J Med Inform. 2021 Dec 09; 158:104662. PMID: 34923448.
      Citations:    
    17. Akbilgic O, Butler L, Karabayir I, Chang PP, Kitzman DW, Alonso A, Chen LY, Soliman EZ. ECG-AI: electrocardiographic artificial intelligence model for prediction of heart failure. Eur Heart J Digit Health. 2021 Dec; 2(4):626-634. PMID: 34993487.
      Citations:    
    18. Dashputre AA, Gatwood J, Sumida K, Thomas F, Akbilgic O, Potukuchi PK, Obi Y, Molnar MZ, Streja E, Kalantar-Zadeh K, Kovesdy CP. Association of dyskalemias with short-term health care utilization in patients with advanced CKD. J Manag Care Spec Pharm. 2021 Oct; 27(10):1403-1415. PMID: 34595956.
      Citations:    
    19. Thomas S, de la Pena P, Butler L, Akbilgic O, Heiferman DM, Garg R, Gill R, Serrone JC. Machine learning models improve prediction of large vessel occlusion and mechanical thrombectomy candidacy in acute ischemic stroke. J Clin Neurosci. 2021 Sep; 91:383-390. PMID: 34373056.
      Citations:    
    20. Dashputre AA, Sumida K, Thomas F, Gatwood J, Akbilgic O, Potukuchi PK, Obi Y, Molnar MZ, Streja E, Kalantar Zadeh K, Kovesdy CP. Association of Dyskalemias with Ischemic Stroke in Advanced Chronic Kidney Disease Patients Transitioning to Dialysis. Am J Nephrol. 2021; 52(7):539-547. PMID: 34289468.
      Citations:    
    21. Chan AWY, Noles DL, Utkov N, Akbilgic O, Smith W. Misalignment between perceptual boundaries and weight categories reflects a new normal for body size perception. Sci Rep. 2021 May 17; 11(1):10442. PMID: 34001935.
      Citations:    
    22. Güntürkün F, Akbilgic O, Davis RL, Armstrong GT, Howell RM, Jefferies JL, Ness KK, Karabayir I, Lucas JT, Srivastava DK, Hudson MM, Robison LL, Soliman EZ, Mulrooney DA. Artificial Intelligence-Assisted Prediction of Late-Onset Cardiomyopathy Among Childhood Cancer Survivors. JCO Clin Cancer Inform. 2021 Apr; 5:459-468. PMID: 33909450.
      Citations:    
    23. Akbilgic O, Shin EK, Shaban-Nejad A. A Data Science Approach to Analyze the Association of Socioeconomic and Environmental Conditions With Disparities in Pediatric Surgery. Front Pediatr. 2021; 9:620848. PMID: 33777865.
      Citations:    
    24. Güntürkün F, Chen D, Akbilgic O, Davis RL, Karabayir I, Strome M, Dai Y, Saraf SL, Ataga KI. Using machine learning to predict rapid decline of kidney function in sickle cell anemia. EJHaem. 2021 May; 2(2):257-260. PMID: 35845269.
      Citations:    
    25. Karabayir I, Akbilgic O, Tas N. A Novel Learning Algorithm to Optimize Deep Neural Networks: Evolved Gradient Direction Optimizer (EVGO). IEEE Trans Neural Netw Learn Syst. 2021 Feb; 32(2):685-694. PMID: 32481228.
      Citations:    
    26. Streja E, Norris KC, Budoff MJ, Hashemi L, Akbilgic O, Kalantar-Zadeh K. The quest for cardiovascular disease risk prediction models in patients with nondialysis chronic kidney disease. Curr Opin Nephrol Hypertens. 2021 Jan; 30(1):38-46. PMID: 33186224.
      Citations:    
    27. Alzubaidi AN, Karabayir I, Akbilgic O, Langham MR. Network Analysis of Postoperative Surgical Complications in a Cohort of Children Reported to the National Surgical Quality Improvement Program: Pediatric. Ann Surg. 2022 Jun 01; 275(6):1194-1199. PMID: 33196492.
      Citations:    
    28. Bunn C, Kulshrestha S, Boyda J, Balasubramanian N, Birch S, Karabayir I, Baker M, Luchette F, Modave F, Akbilgic O. Application of machine learning to the prediction of postoperative sepsis after appendectomy. Surgery. 2021 Mar; 169(3):671-677. PMID: 32951903.
      Citations:    
    29. Karabayir I, Goldman SM, Pappu S, Akbilgic O. Gradient boosting for Parkinson's disease diagnosis from voice recordings. BMC Med Inform Decis Mak. 2020 Sep 15; 20(1):228. PMID: 32933493.
      Citations:    
    30. Mahajan R, Kamaleswaran R, Akbilgic O. Comparative analysis between convolutional neural network learned and engineered features: A case study on cardiac arrhythmia detection. Cardiovasc Digit Health J. 2020; 1(1):37-44. PMID: 35265872.
      Citations:    
    31. Pierre JF, Akbilgic O, Smallwood H, Cao X, Fitzpatrick EA, Pena S, Furmanek SP, Ramirez JA, Jonsson CB. Discovery and predictive modeling of urine microbiome, metabolite and cytokine biomarkers in hospitalized patients with community acquired pneumonia. Sci Rep. 2020 Aug 07; 10(1):13418. PMID: 32770049.
      Citations:    
    32. Akbilgic O, Kamaleswaran R, Mohammed A, Ross GW, Masaki K, Petrovitch H, Tanner CM, Davis RL, Goldman SM. Electrocardiographic changes predate Parkinson's disease onset. Sci Rep. 2020 Jul 09; 10(1):11319. PMID: 32647196.
      Citations:    
    33. Rawal TB, Zahran M, Dhital B, Akbilgic O, Petridis L. The relation between lignin sequence and its 3D structure. Biochim Biophys Acta Gen Subj. 2020 May; 1864(5):129547. PMID: 32032657.
      Citations:    
    34. Gaipov A, Molnar MZ, Potukuchi PK, Sumida K, Szabo Z, Akbilgic O, Streja E, Rhee CM, Koshy SKG, Canada RB, Kalantar-Zadeh K, Kovesdy CP. Acute kidney injury following coronary revascularization procedures in patients with advanced CKD. Nephrol Dial Transplant. 2019 Nov 01; 34(11):1894-1901. PMID: 29986054.
      Citations:    
    35. Willis KA, Purvis JH, Myers ED, Aziz MM, Karabayir I, Gomes CK, Peters BM, Akbilgic O, Talati AJ, Pierre JF. Fungi form interkingdom microbial communities in the primordial human gut that develop with gestational age. FASEB J. 2019 Nov; 33(11):12825-12837. PMID: 31480903.
      Citations:    
    36. Akbilgic O, Obi Y, Potukuchi PK, Karabayir I, Nguyen DV, Soohoo M, Streja E, Molnar MZ, Rhee CM, Kalantar-Zadeh K, Kovesdy CP. Machine Learning to Identify Dialysis Patients at High Death Risk. Kidney Int Rep. 2019 Sep; 4(9):1219-1229. PMID: 31517141.
      Citations:    
    37. Akbilgic O, Davis RL. The Promise of Machine Learning: When Will it be Delivered? J Card Fail. 2019 Jun; 25(6):484-485. PMID: 30978508.
      Citations:    
    38. Kamaleswaran R, Akbilgic O, Hallman MA, West AN, Davis RL, Shah SH. Artificial Intelligence: Progress Towards an Intelligent Clinical Support System. Pediatr Crit Care Med. 2019 Apr; 20(4):399. PMID: 30951001.
      Citations:    
    39. Gyamlani G, Potukuchi PK, Thomas F, Akbilgic O, Soohoo M, Streja E, Naseer A, Sumida K, Molnar MZ, Kalantar-Zadeh K, Kovesdy CP. Vancomycin-Associated Acute Kidney Injury in a Large Veteran Population. Am J Nephrol. 2019; 49(2):133-142. PMID: 30677750.
      Citations:    
    40. Shin EK, Mahajan R, Akbilgic O, Shaban-Nejad A. Sociomarkers and biomarkers: predictive modeling in identifying pediatric asthma patients at risk of hospital revisits. NPJ Digit Med. 2018; 1:50. PMID: 31304329.
      Citations:    
    41. Kamaleswaran R, Akbilgic O, Hallman MA, West AN, Davis RL, Shah SH. Applying Artificial Intelligence to Identify Physiomarkers Predicting Severe Sepsis in the PICU. Pediatr Crit Care Med. 2018 Oct; 19(10):e495-e503. PMID: 30052552.
      Citations:    
    42. Gaipov A, Molnar MZ, Potukuchi PK, Sumida K, Canada RB, Akbilgic O, Kabulbayev K, Szabo Z, Koshy SKG, Kalantar-Zadeh K, Kovesdy CP. Predialysis coronary revascularization and postdialysis mortality. J Thorac Cardiovasc Surg. 2019 Mar; 157(3):976-983.e7. PMID: 31431793.
      Citations:    
    43. Sutton JR, Mahajan R, Akbilgic O, Kamaleswaran R. PhysOnline: An Open Source Machine Learning Pipeline for Real-Time Analysis of Streaming Physiological Waveform. IEEE J Biomed Health Inform. 2019 Jan; 23(1):59-65. PMID: 29994057.
      Citations:    
    44. Kamaleswaran R, Mahajan R, Akbilgic O. A robust deep convolutional neural network for the classification of abnormal cardiac rhythm using single lead electrocardiograms of variable length. Physiol Meas. 2018 Mar 27; 39(3):035006. PMID: 29369044.
      Citations:    
    45. Akbilgic O, Langham MR, Walter AI, Jones TL, Huang EY, Davis RL. A novel risk classification system for 30-day mortality in children undergoing surgery. PLoS One. 2018; 13(1):e0191176. PMID: 29351327.
      Citations:    
    46. Akbilgic O, Langham MR, Davis RL. Race, Preoperative Risk Factors, and Death After Surgery. Pediatrics. 2018 Feb; 141(2). PMID: 29321256.
      Citations:    
    47. Mahajan R, Shin EK, Shaban-Nejad A, Langham MR, Martin MY, Davis RL, Akbilgic O. Disparities in Population-Level Socio-Economic Factors Are Associated with Disparities in Preoperative Clinical Risk Factors in Children. Stud Health Technol Inform. 2018; 255:80-84. PMID: 30306911.
      Citations:    
    48. Mahajan R, Viangteeravat T, Akbilgic O. Improved detection of congestive heart failure via probabilistic symbolic pattern recognition and heart rate variability metrics. Int J Med Inform. 2017 Dec; 108:55-63. PMID: 29132632.
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    49. Viangteeravat T, Akbilgic O, Davis RL. Analyzing Electronic Medical Records to Predict Risk of DIT (Death, Intubation, or Transfer to ICU) in Pediatric Respiratory Failure or Related Conditions. AMIA Jt Summits Transl Sci Proc. 2017; 2017:287-294. PMID: 28815143.
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    50. Asoglu MR, Achjian T, Akbilgiç O, Borahay MA, Kiliç GS. The impact of a simulation-based training lab on outcomes of hysterectomy. J Turk Ger Gynecol Assoc. 2016; 17(2):60-4. PMID: 27403070.
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    51. Humez P, Mayer B, Ing J, Nightingale M, Becker V, Kingston A, Akbilgic O, Taylor S. Occurrence and origin of methane in groundwater in Alberta (Canada): Gas geochemical and isotopic approaches. Sci Total Environ. 2016 Jan 15; 541:1253-1268. PMID: 26476065.
      Citations:    
    52. Akinci OF, Kurt M, Terzi A, Atak I, Subasi IE, Akbilgic O. Natal cleft deeper in patients with pilonidal sinus: implications for choice of surgical procedure. Dis Colon Rectum. 2009 May; 52(5):1000-2. PMID: 19502869.
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    53. Demirkok SS, Basaranoglu M, Akbilgic O. Seasonal variation of the onset of presentations in stage 1 sarcoidosis. Int J Clin Pract. 2006 Nov; 60(11):1443-50. PMID: 17073840.
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