Aysun Cetinyurek Yavuz
Senior Researcher, Radboud University Nijmegen Medical Centre, Nijmegen · Netherlands
Editorial leadership for Journal of Alzheimer's Research and Therapy ISSN 2998-4211
Research interests
- Biotechnology
- Immunology
- Molecular Biology
- Survival Analysis
- Longitudinal Mixed Model Analysis
- Bayesian Statistics
- Penalized B-Splines
- Em Algorithm
Biography
Aysun Cetinyurek Yavuz is a Senior Researcher at Radboud University Nijmegen Medical Centre in Nijmegen, Netherlands. Her research encompasses statistical methodology for survival analysis, including semiparametric frailty models for clustered interval-censored data and Bayesian penalized B-splines for smooth estimation of survival functions and hazard ratios. She has contributed to genetic epidemiology studies examining HLA polymorphisms and allele distributions in various disease contexts, including Henoch-Schönlein purpura, sarcoidosis, and population genetics in Turkish cohorts. Her work extends to clinical research on apical periodontitis, emergency department utilization, and robust statistical methods for non-normal error distributions. Her most-cited publication addresses decision-making criteria and methods for initiating late-stage clinical trials in drug development from a multi-stakeholder perspective.
Selected publications
- Decision‐Making Criteria and Methods for Initiating Late‐Stage Clinical Trials in Drug Development From a Multi‐Stakeholder Perspective: A Scoping Review Recent 2025 cited 7×
- Cardiovascular Benefit of Colchicine in Relation to Baseline Risk: A Secondary Analysis of the LoDoCo2 Trial Recent 2025 cited 6×
- On the Concepts, Methods, and Use of “Probability of Success” for Drug Development Decision‐Making: A Scoping Review Recent 2025 cited 4×
- Angina Severity and Symptom Improvement Are Associated With Diagnostic Acetylcholine Provocation Dose in Vasospastic Angina Recent 2025 cited 3×
- Automated Cardiac Arrest Detection Using Wrist-Worn Photoplethysmography: External Validation in Patients With Induced Shockable Cardiac Arrest (DETECT-1b) Recent 2026
- A machine learning model to detect falls mimicking cardiac arrest-related collapse based on wrist-derived accelerometry: the DETECT-2 study Recent 2026
Ranked by citation impact (Crossref) where available, newest otherwise · verified via ORCID.
Considering JALR for your work?
This journal is guided by Aysun Cetinyurek Yavuz (Senior Researcher, Radboud University Nijmegen Medical Centre, Nijmegen) and a peer-review board of practising researchers. Open access, author-retained copyright (CC BY), and a clear editorial process.