Refreshments: 10:30 AM

Seminar: 11:00 AM

Title: Challenge and issues in biomedical data analysis

Abstract: Biomedical data analysis has become a cornerstone of modern healthcare, driven by rapid advances in high-throughput technologies, electronic health records, medical imaging, and wearable devices. The application of fundamental statistical principles is essential for ensuring valid, reliable, and interpretable results in biomedical research. In practice, researchers are often tasked with comparing and identifying biomarkers that are informative for disease diagnosis and monitoring, as well as evaluating the effectiveness of various treatment procedures and their impact on health outcomes.  After discussing the key issues and challenges encountered during my collaborative research, I will review existing statistical approaches and introduce newly developed semiparametric methods for regression analysis, item reduction, identification of significant exposure factors, and high-dimensional data analysis. These methods aim to improve analytical efficiency and enhance the interpretability of complex biomedical datasets.