Events Calendar

Quantitative Issues in Cancer Research Working Seminar

KRSG 201 (Kresge)

Cathy WangDoctoral Student, Department of Biostatistics, Harvard University"Multi-Study Semi-Supervised Learning: A First Look"ABSTRACT: In many machine learning applications, the gold standard label is difficult or expensive to obtain. Semi-supervised learning (SSL) methods leverage unlabeled data to improve a model’s performance when only limited labeled data is available. We investigate the replicability of the performance of … Continue reading "Quantitative Issues in Cancer Research Working Seminar"

Quantitative Issues in Cancer Research Working Seminar

KRSG 201 (Kresge)

Daniel LiDoctoral Student, Department of Biostatistics, Harvard University"Regularized Best Subset Selection: Concepts for Polygenic Risk Scores and Prediction"ABSTRACT: We will talk about recent developments with regularized best subset selection. We will go over empirical and theoretical results, and discuss important ideas and concepts for applications with a focus on polygenic risk scores. Event Url https://ems.sph.harvard.edu/MasterCalendar/EventDetails.aspx?data=hHr80o3M7J5kCl%2fsdVicuh2HS3V1FSx%2bOywFz%2b%2bsHGske57UtT3x23nPhEMBCNQH

Quantitative Issues in Cancer Research Working Seminar

KRSG 201 (Kresge)

Margaux HujoelDoctoral Student, Department of Biostatistics, Harvard University"Identifiability of a Cancer-resistance Genotypes"ABSTRACT: There is an open question as to whether cancer-resistant genotypes exist (Klein 2009 PNAS). Although individuals who don't develop cancer may lack mutations that make them susceptible, there is an alternative hypothesis that some of these individuals may in fact have genotypes that … Continue reading "Quantitative Issues in Cancer Research Working Seminar"

Quantitative Issues in Cancer Research Working Seminar

KRSG 201 (Kresge)

Eric CohnDoctoral Student, Department of Biostatistics, Harvard University"Micro-Randomized Controlled Trials and Cancer Research"ABSTRACT: The micro-randomized controlled trial (micro-RCT) is an experimental design used to develop and evaluate just-in-time, adaptive interventions. These designs have diverse applications—from rapid-cycle evaluations of mobile health interventions to optimizing cellphone-administered surveys to maximize response rates—many of which are relevant to cancer … Continue reading "Quantitative Issues in Cancer Research Working Seminar"