Fatma Gunturkun, Ph.D.

Senior Biostatisician

Fatma joined the QSU in December of 2022. Prior to QSU, she was a senior biomedical analyst at the University of Tennessee Health Science Center, Center for Biomedical Informatics. She got her PhD in statistics from Dokuz Eylul University, Turkey in 2019.  Her research interests include predictive modeling, ECG signal analysis, medical image analysis, statistical modeling, machine learning, deep learning, and data visualization for clinical decision making.

Methodology Area of Interest:  Machine learning, predictive modeling, data visualization

Clinical Area of Interest: Pediatrics, cardiology, radiology

Selected Publications: 

F Gunturkun, B Bakir-Batu, A Siddiqui et al. Artificial Intelligence-Based Analysis of Pediatric Head Computed Tomography Can Detect Retinal Hemorrhages. JAMA Network Open. 2023;(In Review),1-17.

F Gunturkun, A Khojandi, P Ayvat et al. Characterization and Prediction of Immediate Norepinephrine Response in Critically Ill Adults. Journal of Intensive Care Medicine. 2023;(In Review),1-10.

B Bassa, F Gunturkun, E M Craemer et al. Diabetes, Hypertension, Atrial Fibrillation and Subsequent Stroke-Shift towards Young Ages in Brunei Darussalam. Int. J. Environ. Res. Public Health. 2022;19,8455. Doi: 10.3390/ijerph19148455.

E C Gaudio, N Ammar, F Gunturkun et al. Defining Radiation Treatment Interruption

Rates During the COVID-19 Pandemic: Findings from an Academic Center in an

Underserved Urban Setting. Int J Radiation Oncol Biol Phys. 2022;1−15. Doi:10.1016/j.ijrobp.2022.09.073

I Karabayir, L Butler, S M Goldman, R Kamaleswaran, F Gunturkun et al. Predicting Parkinson’s Disease and its Pathology via Simple Clinical Variables. J Parkinsons Dis. 2022;12(1):341-351. Doi: 10.3233/JPD-212876.

H Hunter, A N West, N Ammar, L Chinthala, F Gunturkun et al. Analyzing Relationships Between Economic and Neighborhood-Related Social Determinants of Health and Intensive Care Unit Length of Stay for Critically Ill Children with Medical Complexity Presenting with Severe Sepsis. Frontiers in Public Health. 2022;10. Doi:10.3389/fpubh.2022.789999.

F Gunturkun, O Akbilgic, R L Davis et al. Artificial Intelligence Assisted Prediction of Late Onset Cardiomyopathy among Childhood Cancer Survivor. JCO Journal of Clinical Cancer Informatics. 2021;4,459-468.

F Gunturkun, D Chen, O Akbilgic et al. Using Machine Learning to Predict Rapid Decline of Kidney Function in Sickle Cell Anemia. British Journal of Haematology. 2021;2(2),257-260.

F Gode, T Bodur, F Gunturkun, et al. Comparison of Microfluid Sperm Sorting Chip and Density Gradient Methods for Use in Intrauterine Insemination Cycles. Fertility and Sterility; 2019.

F Gunturkun, O Cilengiroglu. Risk Adjusted Hospital Mortality Prediction Model: A Case Study in a Turkish Training Research Hospital. Hacettepe Journal of Mathematics and Statistics; 2019.