Statistical methodology research focuses on survival analysis, longitudinal data analysis, machine learning, meta-analysis and study designs. My applied research interests include the study of cancer, radiology, transmittable disease, heart diseases, environmental health and health behavior.
My colleagues and I want to answer specific research questions by performing advanced statistical methodology to find the unknown risk features of fatal diseases and chronic conditions.
We have uncovered several notable discoveries in our lab, such as refractory hypertension not being categorized by excess aldosteronism or larger fluid retention related to controlled resistance hypertension (RHTN). If confirmed, this would have important implications for patients' clinical management in that continued titration of diuretic therapy and/or mineralocorticoid receptor antagonists may not be appropriate. It may even be counterproductive because it may activate reflexive pressor responses and may raise the risk of adverse events.
In addition, our paper Quantitative MRI of fatty liver disease in a large pediatric cohort: correlation between liver fat fraction, stiffness, volume, and patient-specific factors reports that the liver volume, stiffness and fat fraction are linked and related to various patient-specific features. These connections require further study since magnetic resonance imaging (MRI) is gradually utilized as a non-invasive biomarker for fatty liver disease diagnosis and examination.
I’ve held various positions, including lead statistician for the Collaborative Antiviral Study Group (CASG) and deputy director of the Statistical and Data Management Center of Mycoses Study Group (MSG). I’ve also been a Steering Committee member for the Consortium of Hospitals to Advance Research on Tobacco (CHART) trials.
I enjoy applying what I’ve learned and developing new methods to improve people’s health. Additionally, I have received multiple awards and recognitions throughout my career, including:
I have more than 10 years’ experience in biostatistics and joined the team at Cincinnati Children’s in 2012. My research has been published in a multitude of journals, such as Biometrics, Radiology, Journal of Hip Preservation Surgery, Hypertension and Journal of the American College of Radiology.
BS: University of Science and Technology of China, Hefei, Anhui, China.
PhD: University of Missouri, Columbia, MO.
Biostatistics and Epidemiology
Pectus excavatum: the effect of tricuspid valve compression on cardiac function. Pediatric Radiology: roentgenology, nuclear medicine, ultrasonics, CT, MRI. 2024; 54:1462-1472.
Association Between MR Elastography Liver Stiffness and Histologic Liver Fibrosis in Children and Young Adults With Autoimmune Liver Disease. American Journal of Roentgenology. 2024; 223:e2431108.
Impact of a relocation to a new critical care building on pediatric safety events. Journal of hospital medicine (Online). 2024; 19:589-595.
Fetal magnetic resonance imaging, ultrasound, and echocardiography findings in twin reversed arterial perfusion sequence. Pediatric Radiology: roentgenology, nuclear medicine, ultrasonics, CT, MRI. 2024; 54:702-714.
Accuracy of CT perfusion-predicted core in the late window. Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences. 2024; 30:250-254.
Clinical impacts of the rapid diagnostic method on positive blood cultures. Laboratory Medicine. 2024; 55:179-184.
Multiuser immersive virtual reality simulation for interprofessional sepsis recognition and management. Journal of hospital medicine (Online). 2024; 19:185-192.
Revisiting Post-ICU Admission Fluid Balance Across Pediatric Sepsis Mortality Risk Strata: A Secondary Analysis of a Prospective Observational Cohort Study. Critical Care Explorations. 2024; 6:e1027.
Gadolinium-based contrast media does not improve the staging of neuroblastoma image-defined risk factors at diagnosis. Pediatric Blood and Cancer. 2024; 71:e30724.
Using MRI-derived observed-to-expected total fetal lung volume to predict lethality in fetal skeletal dysplasia. Pediatric Radiology: roentgenology, nuclear medicine, ultrasonics, CT, MRI. 2024; 54:43-48.