Events Calendar

Quantitative Issues in Cancer Research Working Group Seminar

In Person

Christian Covington, PhD Student, Department of Biostatistics, Harvard T.H. Chan School of Public Health Statistical theory and the practice of data analysis: A brief and biased history Abstract: This talk gives an account of the replication crisis and how different disciplines– namely applied sciences, statistics, and theoretical computer science (TCS), have developed their own research … Continue reading "Quantitative Issues in Cancer Research Working Group Seminar"

Quantitative Issues in Cancer Research Working Group Seminar

In Person

Elizabeth Graff, PhD Student, Department of Biostatistics, Harvard T.H. Chan School of Public Health Applications of Deep Learning for Graph-Structured Data: From Disease Spread to Social Networks Abstract: How can we apply deep learning to solve problems in modeling the spread of disease? In this talk, we will explore the components and applications of Graph … Continue reading "Quantitative Issues in Cancer Research Working Group Seminar"

Quantitative Issues in Cancer Research Working Group Seminar

In Person

Kimberly Greco, PhD Student, Department of Biostatistics, Harvard T.H. Chan School of Public Health Graph Attention Framework to Enhance Rare Disease Sub-Phenotyping from EHR Abstract: Accurately sub-phenotyping patients according to their risk for an adverse clinical outcome can significantly enhance clinical decision-making. Recent advances in patient representation learning have enabled the development of sophisticated clustering … Continue reading "Quantitative Issues in Cancer Research Working Group Seminar"

Quantitative Issues in Cancer Research Working Group Seminar

In Person

Carmen B. Rodriguez, PhD Student, Department of Biostatistics, Harvard T.H. Chan School of Public Health A Bayesian Mixture Model Approach to Examining Socioeconomic Disparities in Endometrial Cancer Care in Massachusetts. Abstract: Endometrial cancer (EC) is the most common gynecologic cancer in the United States. On average, African American women have 55% higher 5-year mortality risk … Continue reading "Quantitative Issues in Cancer Research Working Group Seminar"

Quantitative Issues in Cancer Research Working Group Seminar

In Person

Daniel Schwartz, Postdoctoral Research Fellow, Department of Biostatistics, Harvard University Dynamic Latent Factor Models To Infer Dietary Patterns From Nutrition Survey Data Abstract: A growing body of research has shown that poor diet is a leading risk factor for death, especially in connection with chronic diseases such as cardiovascular disease. However, these studies provide limited … Continue reading "Quantitative Issues in Cancer Research Working Group Seminar"

Quantitative Issues in Cancer Research Working Group Seminar

In Person

Christian Covington, PhD Student, Department of Biostatistics, Harvard T.H. Chan School of Public Health Multiverse Analysis for Causal Inference (and vice versa) Abstract: Multiverse analysis is a framework developed in the quantitative social and behavioral sciences, designed to represent “non-statistical” uncertainty that arises in data analysis when making choices about conceptual operationalization, data preparation, etc. … Continue reading "Quantitative Issues in Cancer Research Working Group Seminar"