Wang Lab
Dr. Wang’s laboratory focuses on the intersection of machine learning and medical imaging. The lab develops and applies methods in machine learning, artificial intelligence, and data science to process and analyze medical images to understand the mechanisms of diseases and build diagnostic/predictive models.
Highlights
Biomarkers identified by interpretable ML model
Brain Age Prediction Pipeline
Predict overall survival in patients with metastatic prostate cancer
Pipeline of Alzheimer’s Disease Diagnosis
Pipeline flow chart of automatic LGN segmentation
Latest News
- Sep 29, 2026: We are excited to share our new study, “Predicting the Timing of Adolescent Drinking Onset from Baseline Clinical Data: A Stacked-Encoder Survival Framework with Embedding-Derived Biotypes.” Congratulations to Ruobing and the entire team on this new achievement!
- Sep 28, 2026: Esther presents a poster on "Early AI Prediction of Survival in Metastatic Castration-Resistant Prostate Cancer Using Tumor Growth Rate" at the Great Plains Bioinformatics Conference 2026.
- Sep 25, 2026: We are excited to share our new preprint, “Towards Whole-Study Screening for Congenital Heart Disease,” now available on arXiv. Congratulations to Azzam and all co-authors!
- Sep 11, 2026: We are pleased to share that our study, “Classification of Adolescent Drinking via Behavioral, Biological, and Environmental Variables: A Machine Learning Approach with Bias Control,” is now published in Addiction Biology. Congratulations to Ruobing and all co-authors on this achievement!
- Sep 01, 2026: We are excited to share that our manuscript, “Classification of Adolescent Drinking via Behavioral, Biological, and Environmental Variables: A Machine Learning Approach with Bias Control,” has been accepted for publication in Addiction Biology. Congratulations to Ruobing and all co-authors on this achievement!