Frontiers in Biostatistics: Group Sequential Design Assuming Delayed Benefit

February 9, 2021 1:00PM ET Keaven Anderson, PhD Scientific AVP, Methodology Research, Biostatistics at Merck Group Sequential Design Assuming Delayed Benefit Abstract: We consider an asymptotic approach to design of group sequential trials with a potentially delayed effects. Logrank, weighted logrank tests and combination tests are of primary interest, but we also consider restricted mean […]

Data Science Zoominar: Diversity and Ethics in Genomics

Tuesday February 23, 2021 1:00PM Eastern Time A conversation with Keolu Fox, PhD Assistant Professor, Department of Anthropology, University of California, San Diego Moderator: Aedin Culhane YouTube Link: https://www.youtube.com/watch?v=VANlStOnFPY

Frontiers in Biostatistics: Distributed Statistical Learning and Inference in EHR and Other Healthcare Datasets

Frontiers in Biostatistics Seminar March 9, 2021 1:00PM Rui Duan, PhD Assistant Professor of Biostatistics Harvard TH Chan School of Public Health Distributed Statistical Learning and Inference in EHR and Other Healthcare Datasets Abstract: The growth of availability and variety of healthcare data sources has provided unique opportunities for data integration and evidence synthesis, which […]

Data Science Zoominar: The Importance of Representative Samples in Clinical Trials

Tuesday March 23, 2021 1:00PM Eastern Time A conversation with Timothy Rebbeck Vincent L. Gregory, Jr. Professor of Cancer Prevention, Epidemiology, Harvard T.H. Chan School Of Public Health Professor, Medical Oncology, Dana-Farber Cancer Institute Moderator: Rafael Irizarry YouTube Link: https://www.youtube.com/watch?v=Q4uBibxGf20

Frontiers in Biostatistics: Single-Cell RNA-Seq Data Analysis Via a Regularized Zero-Inflated Mixture Model Framework

Frontiers in Biostatistics Seminar May 11, 2021 1:00PM Jianhua Hu, PhD Professor, Biostatistics (in Medicine and in the Herbert Irving Comprehensive Cancer Center) Director, Cancer Biostatistics Program Columbia University Register at: http://bit.ly/FIBMay21 Abstract: Applications of single-cell RNA sequencing in various biomedical research areas have been blooming. This new technology provides unprecedented opportunities to study disease […]

Training Session: Efficient Phase I Clinical Trial Design

May 19, 2021 10:00am-12:00PM Eastern Time Fangxin Hong, PhD Senior Research Scientist Department of Data Science, Dana-Farber Cancer Institute Department of Biostatistics, Harvard T.H. Chan School of Public Health    

Data Science Seminar: Causal Inference Methods for Measures of Health Disparities

Thursday, October 28, 2021 11:00am Eastern Time Tengfei Li Georgetown University Causal Inference Methods for Measures of Health Disparities There is increased interest in the evaluation of health disparities between different socioeconomic groups using data from observational studies. However, in the absence of randomization, the results and conclusions may be limited to associations rather than […]

Postdoc Recruitment Day

The Dana-Farber Cancer Institute Department of Data Science announces its second annual Postdoc Recruitment Day to be held on Wednesday, November 3rd from 1-3pm EST. If you are interested in learning more about postdoctoral opportunities at Dana-Farber Cancer Institute and would like to learn about the research our faculty are conducting, please sign up for […]

Frontiers in Biostatistics: A Bayesian Phase I/II Trial Design for Immunotherapy

Tuesday, November 9, 2021 1:00pm Eastern Time Suyu Liu, PhD Associate Professor Department of Biostatistics The University of Texas MD Anderson Cancer Center A Bayesian Phase I/II Trial Design for Immunotherapy Immunotherapy is an innovative treatment approach that stimulates a patient's immune system to fight cancer. It demonstrates characteristics distinct from conventional chemotherapy and stands […]

Frontiers in Biostatistics: Cancer on the Way to Mars

Tuesday, December 7, 2021 1:00pm Eastern Time Giovanni Parmigiani, PhD Professor Harvard T.H. Chan School of Public Health Link to YouTube Video Cancer on the Way to Mars Links: https://www.nap.edu/download/26155 https://www.env.go.jp/en/chemi/rhm/basic-info/index.html https://www.nasa.gov/feature/goddard/real-martians-how-to-protect-astronauts-from-space-radiation-on-mars https://www.nasa.gov/sites/default/files/atoms/files/space_radiation_ebook.pdf https://standards.nasa.gov/standard/nasa/nasa-std-3001-vol-1 https://spaceradiation.larc.nasa.gov/nasapapers/2020/5008710.pdf

Frontiers in Biostatistics: Studies on COVID-19 and Cancer using National Real-World VA Data

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 […]

2022 DF/HCC Celebration of Early Career Investigators in Cancer Research

January 19 | 2022 | 1-4PM Eastern Time This annual symposium showcases the talent of early career investigators at the Dana-Farber/Harvard Cancer Center who work in population science, including epidemiology, biostatistics, outcomes, diversity, and cancer care delivery research, and early detection. This year, Ann Partridge, MD, MPH will be our keynote speaker. Dr. Partridge is […]

Data Science Seminar: Deciphering Tissue Microenvironment from Next Generation Sequencing Data

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 […]

Frontiers in Biostatistics: Early Phase Design Considerations for Oncology Drug Development in the Era of Immunotherapy and Targeted Agents

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 […]

Data Science Seminar: End-to-end AI for Screening Mammography

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 […]

Data Science Seminar: Spatial meshing for general Bayesian multivariate models

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 […]

Data Science Seminar: From descriptive to predictive biology via single-cell multiomics

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 […]

Frontiers in Biostatistics: Considerations for Extracting Real-World Evidence from Real-World Data

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 […]

Data Science Seminar: Radiomics for Feature Extraction from Radiological Images

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 […]

Data Science Seminar: Engineering Protease Activity Sensors For Personalized Detection and Profiling of Cancer

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. […]

2022 Marvin Zelen Symposum: Data Visualization

The growing availability of informative datasets and software tools has led to increased reliance on data visualizations across many industries, academia, and government. News organizations are increasingly embracing data journalism and including effective infographics as part of their reporting, while in research we increasingly rely on data visualization to assess data quality and describe and […]

Frontiers in Biostatistics: Tree-based Ensembling Strategies for Handling Heterogeneous Data

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 […]