Dr. Zhu's research focuses on developing statistical methods for biomarkers and electronic medical records. She works on methods that combine biomarkers to predict cognitive decline related to preclinical Alzheimer’s Disease among normal individuals. She also develops methods to evaluate misdiagnosis-related harm at institution or medical system levels using electronic medical records.
Methodologically, Dr. Zhu is interested in tree-based models, latent variable models, survival analysis, and recurrent event analysis. Dr. Zhu's general interest is in interpretable and robust statistical methodology that advances biomedical understanding and informs practices.
Experiences & Accomplishments
Yuxin (Daisy) Zhu, PhD, works on statistical methods related to tree-based models, latent variable models, survival analysis, and recurrent event analysis. Her general interest is in interpretable and robust statistical methodology that advances biomedical understanding and informs practices.
Zhu Y, Wang MC. Obtaining optimal cutoff values for tree classifiers using multiple biomarkers. Biometrics. 2022 Mar;78(1):128-40.
Wang MC, Zhu Y. Bias correction via outcome reassignment for cross-sectional data with binary disease outcome. Lifetime Data Analysis. 2022 Oct;28(4):659-74.
Zhu Y, Wang Z, Newman‐Toker D. Misdiagnosis‐related harm quantification through mixture models and harm measures. Biometrics. 2022 Oct 11.
Wang Z, Tang Z, Zhu Y, Pettigrew C, Soldan A, Gross A, Albert M. AD risk score for the early phases of disease based on unsupervised machine learning. Alzheimer's & Dementia. 2020 Nov;16(11):1524-33.
Albert M, Zhu Y, Moghekar A, Mori S, Miller MI, Soldan A, Pettigrew C, Selnes O, Li S, Wang MC. Predicting progression from normal cognition to mild cognitive impairment for individuals at 5 years. Brain. 2018 Mar 1;141(3):877-87.