Tuesday September 14, 2021 1:00PM Eastern Time Holly Janes, Ph.D. Professor, Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center Professor, Public Health Sciences Division, Fred Hutchinson Cancer Research Center YouTube video now available.
Tuesday, October 19, 2021 1:00pm Eastern Time Meredith Regan, ScD Associate Professor Department of Data Science, Dana-Farber Cancer Institute, Harvard Medical School Treatment-free Survival as a Novel Outcome Measure of Immuno-oncology-based Therapy YouTube Link
Nathanael Fillmore is the Associate Director for Machine Learning and Advanced Analytics at the VA Boston Healthcare System’s Cooperative Studies Program Informatics Center. He leads a data science team focused on using machine learning and data science methods, in combination with the VA’s large clinical, genomic, and imaging databases, to generate knowledge and resources that […]
Friday February 4, 2022 1:00PM Eastern Time Register. Jian Hu PhD Candidate, Department of Biostatistics, Epidemiology and Informatics University of Pennsylvania ABSTRACT: The advent of high-throughput next-generation sequencing (NGS) technologies has transformed our understanding of cell biology and human disease. As NGS has been adopted earliest by the scientific community, its use has now become […]
Tuesday, February 8, 2022 1:00pm Eastern Time YouTube Video Elizabeth Garrett-Mayer, PhD, FSCT Vice President Center for Research and Analytics (CENTRA) Dr. Garrett-Mayer joined ASCO in 2017 as CENTRA’s Division Director for Biostatistics and Research Data Governance and became CENTRA’s first Vice President in 2022. CENTRA leads ASCO’s research efforts, including the TAPUR Study, ASCO’s […]
Tuesday February 15, 2022 1:00PM Eastern Time William Lotter, PhD Vice President of Machine Learning, RadNet, Inc. Chief Technology Officer & Co-Founder, DeepHealth, Inc. Register. Screening mammography has been estimated to reduce breast cancer mortality by 20-40%, but significant opportunities remain for improving access and overall quality. Artificial intelligence (AI) has the potential to deliver […]
Thursday February 24, 2022 1:00PM Eastern Time Michele Peruzzi, PhD Postdoctoral Associate, Department of Statistical Science, Duke University Register. Abstract: In this talk, I will consider the problem of fitting Bayesian models with spatial random effects to large scale multivariate multi-type data from satellite imaging, land-based weather and air quality sensors, and citizen science, with […]
Monday February 28, 2022 1:00PM Eastern Time Genevieve Stein-O'Brien Instructor, Johns Hopkins University, School of Medicine Department of Oncology, Division of Biostatistics and Bioinformatics; Department of Neuroscience; and McKusick-Nathans Department of Genomic Medicine Assistant Director, Johns Hopkins University Single Cell Consortium Register. Abstract: As the single-cell field races to characterize each cell type, state, and […]
Tuesday, March 1, 2022 1:00pm Eastern Time Rebecca A. Hubbard, PhD Professor of Biostatistics University of Pennsylvania Perlman School of Medicine YouTube Video Abstract: Opportunities to use real-world data (RWD), including electronic health records (EHR) and medical claims data, have exploded over the past decade. The Covid-19 pandemic has provided a particularly dramatic illustration of […]
Friday, March 4, 2022 12:00PM Eastern Time Ani Eloyan, PhD Assistant Professor Department of Biostatistics, Brown University Register. Abstract: Cancer patients routinely undergo radiological evaluations where images of various modalities including computed tomography, positron emission tomography, and magnetic resonance images are collected for diagnosis and for evaluation of disease progression. Tumor characteristics, often referred to […]
Monday March 7th, 2022 1:00PM Eastern Time Ava Soleimany, PhD Senior Researcher, Biomedical Machine Learning Group at Microsoft Research, New England Abstract: Precision cancer medicine envisions a world where diagnostic and therapeutic opportunities are intelligently tailored to individual patient needs. Achieving this vision necessitates access to high quality, accurate, and individualized information about disease state. […]
Maya Ramchandran Data Scientist, ZephyrAI Abstract: Adapting machine learning algorithms to better handle clustering or other partition structure within training data sets is important across a wide variety of biological applications. We first consider the task of learning prediction models when multiple training studies are available. We present a novel weighting approach for constructing tree-based ensemble […]
