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DTSTART;TZID=America/New_York:20230329T130000
DTEND;TZID=America/New_York:20230329T140000
DTSTAMP:20260412T105213
CREATED:20230120T174649Z
LAST-MODIFIED:20230329T184122Z
UID:3949-1680094800-1680098400@ds.dfci.harvard.edu
SUMMARY:Dimension Reduction of Longitudinal Microbiome Data
DESCRIPTION:Frontiers in Biostatistics Seminar \nWednesday March 29\, 2023\n1:00PM Eastern Time \nPixu Shi\, PhD\nAssistant Professor of Biostatistics & Bioinformatics\nDivision of Integrative Genomics\nDepartment of Biostatistics & Bioinformatics\nDuke University School of Medicine \nAbstract:\nThe analysis of longitudinal microbiome is crucial to the understanding of how microbiome changes over time. It often requires careful maneuver of high dimensional microbial features\, missing samples and varying time points across subjects. Longitudinal microbiome data can often be formatted into a high-dimensional order-3 tensor with three modes representing the subject\, time\, and bacteria respectively. In this talk\, we present functional tensor SVD\, a dimension reduction tool that can uncover sub-population structures in subjects\, compress high-dimensional features into low-dimensional trajectories\, and extract shared temporal patterns among features\, all without imputation of missing samples or rounding of time points. We will demonstrate the robust performance of our method through simulations and multiple case studies.
URL:https://ds.dfci.harvard.edu/event/dimension-reduction-of-longitudinal-microbiome-data/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2023/01/Pixu_profile_square.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230407T130000
DTEND;TZID=America/New_York:20230407T170000
DTSTAMP:20260412T105213
CREATED:20230216T194917Z
LAST-MODIFIED:20230410T125358Z
UID:4043-1680872400-1680886800@ds.dfci.harvard.edu
SUMMARY:Machine Learning in Medical Imaging: From New Techniques to Clinical Translation
DESCRIPTION:Zelen 2023 Program \nThe 2023 Marvin Zelen Memorial Symposium featuring talks by: \n\nAndy Beck (Co-founder & CEO\, Path AI)\nEmerging Methods in Machine Learning and Applications for Digital Pathology\nJonathan Chen (Instructor in Pathology\, MGH)\nMulticellular Networks: Immunity Hubs in Human NSCLC\nMarzyeh Ghassemi (Assistant Professor\, MIT)\nDesigning Machine Learning Processes For Equitable Health Systems\nPolina Golland (Professor\, MIT)\nLearning to Read X-ray: Applications to Heart Failure Monitoring\nJayashree Kalpathy-Cramer (Professor\, University of Colorado\, MGH\, and HMS)\nOpportunities and Challenges for Medical Imaging AI – Lessons from Oncology and Ophthalmology\nBill Lotter (Member of the Faculty\, DFCI and HMS)\nAI for Mammography: From Algorithms to Clinical Integration\nShantanu Singh (Senior Group Leader\, Broad Institute)\nFortune-telling with Images: Painting Cells for Discovering Drugs\n\nFriday April 7\, 2023\n1:00-5:00PM \nSimmons University\nParesky Conference Center\n300 The Fenway\, Boston\, MA \nReception to follow. \nRegister for virtual or in-person attendance.
URL:https://ds.dfci.harvard.edu/event/machine-learning-in-medical-imaging-from-new-techniques-to-clinical-translation/
LOCATION:Simmons University\, 300 The Fenway\, Boston\, MA\, United States
CATEGORIES:Conference
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2023/02/Zelen-2023-Instagram-Post-Square-e1680115209110.png
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230509T130000
DTEND;TZID=America/New_York:20230509T140000
DTSTAMP:20260412T105213
CREATED:20230410T125338Z
LAST-MODIFIED:20230515T123922Z
UID:4170-1683637200-1683640800@ds.dfci.harvard.edu
SUMMARY:Model-robust and Efficient Covariate Adjustment for Cluster-randomized Experiments
DESCRIPTION:Frontiers in Biostatistics Seminar \nTuesday May 9\, 2023\n1:00PM Eastern Time \nJoin the Zoom. \nFan Li\, PhD\nAssistant Professor of Biostatistics\, Yale School of Public Health \nCluster-randomized experiments are increasingly used to evaluate interventions in routine practice conditions\, and researchers often adopt model-based methods with covariate adjustment in the statistical analyses. However\, the validity of model-based covariate adjustment is unclear when the working models are misspecified\, leading to ambiguity of estimands and risk of bias. In this article\, we first adapt two conventional model-based methods\, generalized estimating equations and linear mixed models\, with weighted g-computation to achieve robust inference for cluster-average and individual-average treatment effects. Furthermore\, we propose an efficient estimator for each estimand that allows for flexible covariate adjustment and additionally addresses cluster size variation dependent on treatment assignment and other cluster characteristics. Such cluster size variations often occur post-randomization and\, if ignored\, can lead to bias of model-based estimators. For our proposed estimator\, we prove that when the nuisance functions are consistently estimated by machine learning algorithms\, the estimator is consistent\, asymptotically normal\, and efficient. When the nuisance functions are estimated via parametric working models\, the estimator is triply-robust. Simulation studies and analyses of three real-world cluster-randomized experiments demonstrate that the proposed methods are superior to existing alternatives.
URL:https://ds.dfci.harvard.edu/event/model-robust-and-efficient-covariate-adjustment-for-cluster-randomized-experiments/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2023/04/fanli-scaled-e1681131195600.jpeg
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BEGIN:VEVENT
DTSTART;VALUE=DATE:20230802
DTEND;VALUE=DATE:20230805
DTSTAMP:20260412T105213
CREATED:20230515T123912Z
LAST-MODIFIED:20230515T123912Z
UID:4247-1690934400-1691193599@ds.dfci.harvard.edu
SUMMARY:BioC2023: the Bioconductor Annual Conference
DESCRIPTION:We are incredibly excited that Bioc2023 the annual Bioconductor meeting will be in Boston at the Dana-Farber Cancer Institute from August 2-4. It is a hybrid meeting to enable maximum outreach to our global community. Registration is now open and scholarships are available.  \nContact us for sponsorship opportunities.  \nSpeakers include: \n\nJJ Allaire (Founder and CEO of RStudio\, Posit PBC)\nHeng Li (Associate Professor\, Dana-Farber Cancer Institute\, Harvard Medical School)\nBeth Cimini (Senior Group Leader\, Broad Institute of MIT & Harvard)\nJeffrey Moffitt (Assistant Professor\, Harvard Medical School and Boston Children’s Hospital) \nSam Lent (Senior Computational Biologist at Freenome)\n\nConnect with talented R/Bioconductor users & developers\, data scientists\, biostatisticians\, and bioinformaticians at #Bioc2023
URL:https://ds.dfci.harvard.edu/event/bioc2023-the-bioconductor-annual-conference/
LOCATION:Dana-Farber Cancer Institute\, 450 Brookline Ave\, Boston\, MA\, 02215\, United States
CATEGORIES:Conference
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230926T100000
DTEND;TZID=America/New_York:20230926T110000
DTSTAMP:20260412T105213
CREATED:20230825T175051Z
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UID:4458-1695722400-1695726000@ds.dfci.harvard.edu
SUMMARY:Forecasting pancreatic carcinogenesis from spatial multi-omics
DESCRIPTION:Frontiers in Biostatistics Seminar \nTuesday September 26\, 2023 @ 10am ET\nCenter for Life Sciences Building\, Room 11081 \nElana Fertig\, PhD\nDivision Director of Oncology Quantitative Sciences\, Professor of Oncology\nJohns Hopkins University \nYouTube Video \nCombining genomics with mathematical modeling provides a forecast system that can yield computational predictions to anticipate cancer progression and therapeutic response. High-throughput profiling technologies can indicate the molecular and cellular pathways of malignancies\, but not the effect of targeting those pathways with therapy. Precision interception requires relating therapies to the cellular phenotypes underlying pancreatic carcinogenesis. This talk presents a hybrid computational and experimental strategy to uncover interactions between neoplastic cells and the microenvironment during pancreatic carcinogenesis. As pancreatic cancer develops\, it forms a complex microenvironment of multiple interacting cells. The microenvironment of advanced pancreatic cancer includes a heterogeneous and dense population of cells\, such as macrophages and fibroblasts\, that are associated with immunosuppression. New single-cell and spatial molecular profiling technologies enable unprecedented characterization of the cellular and molecular composition of the microenvironment. These technologies provide the potential to identify candidate therapeutics to intercept immunosuppression in pancreatic cancer. State-of-the-art mathematical approaches in computational biology are essential to uncover mechanistic insights for high-throughput data for these precision interception strategies. \n  \nWant to get our weekly events newsletter? Click here!
URL:https://ds.dfci.harvard.edu/event/forecasting-pancreatic-carcinogenesis-from-spatial-multi-omics/
LOCATION:Center of Life Sciences\, Room 11081\, 3 Blackfan Circle\, Boston\, MA\, 02215\, United States
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2023/08/headshot-copy.jpg
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231024T130000
DTEND;TZID=America/New_York:20231024T140000
DTSTAMP:20260412T105213
CREATED:20230825T175528Z
LAST-MODIFIED:20231031T115135Z
UID:4463-1698152400-1698156000@ds.dfci.harvard.edu
SUMMARY:AI in Medical Imaging: Current State & Future Opportunities
DESCRIPTION:Frontiers in Biostatistics Seminar \nTuesday October 24\, 2023 @ 1pm ET\nCenter for Life Sciences Building\, Room 11081 \nWilliam Lotter\, PhD\nAssistant Professor\, Dana-Farber Cancer Institute and Harvard Medical School \nYouTube Video \nWant to get our weekly events newsletter? Click here!
URL:https://ds.dfci.harvard.edu/event/frontiers-in-biostatistics-william-lotter/
LOCATION:Center of Life Sciences\, Room 11081\, 3 Blackfan Circle\, Boston\, MA\, 02215\, United States
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2022/08/Bill_Lotter_headshot-scaled-e1659653586370.jpg
GEO:42.3394159;-71.104234
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231108T120000
DTEND;TZID=America/New_York:20231108T130000
DTSTAMP:20260412T105213
CREATED:20231030T131716Z
LAST-MODIFIED:20231030T131847Z
UID:4616-1699444800-1699448400@ds.dfci.harvard.edu
SUMMARY:Single-cell Multiomic Exploration of Oncogenic and Immunologic Programs in Melanoma and CLL
DESCRIPTION:Elevate @ Eleven: Comp Bio Connections \nWednesday November 8th\, 2023\n12:00-1:00PM\nIn-person only\, Zelen Commons\, 11th floor of the Center for Life Sciences Building \nJeremy Simon\nSenior Research Scientist\, Harvard T.H. Chan School of Public Health \nLunch is provided. \n 
URL:https://ds.dfci.harvard.edu/event/single-cell-multiomic-exploration-of-oncogenic-and-immunologic-programs-in-melanoma-and-cll/
LOCATION:Center for Life Sciences\, Zelen Commons\, 3 Blackfan Circle\, Boston\, MA\, 02115
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2023/01/Jeremy-Simon-600x600-1-e1673981068499.jpeg
GEO:42.3394159;-71.104234
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231205T130000
DTEND;TZID=America/New_York:20231205T140000
DTSTAMP:20260412T105213
CREATED:20230901T114137Z
LAST-MODIFIED:20231208T201749Z
UID:4488-1701781200-1701784800@ds.dfci.harvard.edu
SUMMARY:Analyzing Big EHR Data - Optimal Cox Regression Subsampling Procedure with Rare Events
DESCRIPTION:Frontiers in Biostatistics Seminar \nTuesday December 5\, 2023 @ 1pm ET\nYouTube Link \nMalka Gorfine\, PhD\nProfessor\, Department of Statistics\,  Tel Aviv University\, Israel \nAbstract: Massive sized survival datasets become increasingly prevalent with the development of the healthcare industry\, and pose computational challenges unprecedented in traditional survival analysis use cases. In this work we analyze the UK-biobank colorectal cancer data with genetic and environmental risk factors\, including a time-dependent coefficient\, which transforms the dataset into “pseudo-observation” form\, thus critically inflating its size. A popular way for coping with massive datasets is downsampling them\, such that the computational resources can be afforded by the researcher. Cox regression has remained one of the most popular statistical models for the analysis of survival data to-date. This work addresses the settings of right censored and possibly left-truncated data with rare events\, such that the observed failure times constitute only a small portion of the overall sample. We propose Cox regression subsampling-based estimators that approximate their full-data partial-likelihood-based counterparts\, by assigning optimal sampling probabilities to censored observations\, and including all observed failures in the analysis. The suggested methodology is applied on the UK-biobank for building a colorectal cancer risk-prediction model\, while reducing the computation time and memory requirements. We establish asymptotic properties under suitable conditions and develop a framework for determining the optimal subsample size. \nWant to get our weekly events newsletter? Click here!
URL:https://ds.dfci.harvard.edu/event/frontiers-in-biostatistics-seminar-malka-gorfine/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2023/09/portrait.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231206T120000
DTEND;TZID=America/New_York:20231206T130000
DTSTAMP:20260412T105213
CREATED:20231121T123117Z
LAST-MODIFIED:20231121T123117Z
UID:4661-1701864000-1701867600@ds.dfci.harvard.edu
SUMMARY:The Splicing Factor CCAR1 Regulates the Fanconi Anemia/BRA Pathway
DESCRIPTION:Elevate @ Eleven: Comp Bio Connections \nWednesday December 6th\, 2023\n12:00-1:00PM\nIn-person only\, Zelen Commons\, 11th floor of the Center for Life Sciences Building \nHuy Nguyen\nComputational Biologist\, Center for DNA Damage & Repair\, Dana-Farber Cancer Institute \nLunch is provided. \n 
URL:https://ds.dfci.harvard.edu/event/the-splicing-factor-ccar1-regulates-the-fanconi-anemia-bra-pathway/
LOCATION:Center for Life Sciences\, Zelen Commons\, 3 Blackfan Circle\, Boston\, MA\, 02115
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2023/11/huy_square.png
GEO:42.3394159;-71.104234
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240110T120000
DTEND;TZID=America/New_York:20240110T130000
DTSTAMP:20260412T105213
CREATED:20240104T202615Z
LAST-MODIFIED:20240104T202615Z
UID:4773-1704888000-1704891600@ds.dfci.harvard.edu
SUMMARY:ImmunoPROFILE: An Multiplex Immunofluorescence Based Immune Cell Profiling Test and Data Resource; An Overview and Analysis Vignette Using GNNs
DESCRIPTION:Elevate @ Eleven: Comp Bio Connections \nWednesday January 10th\, 2023\n12:00-1:00PM\nIn-person only\, Zelen Commons\, 11th floor of the Center for Life Sciences Building \nKatharina Hoebel\, Research Fellow\, Department of Data Science\, Dana-Farber Cancer Institute\nJames Lindsay\, Director\, Software Engineer\, Department of Data Science\, Dana-Farber Cancer Institute \nLunch is provided.
URL:https://ds.dfci.harvard.edu/event/immunoprofile-an-multiplex-immunofluorescence-based-immune-cell-profiling-test-and-data-resource-an-overview-and-analysis-vignette-using-gnns/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2024/01/katharina_james2.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240116T130000
DTEND;TZID=America/New_York:20240116T140000
DTSTAMP:20260412T105213
CREATED:20230927T113715Z
LAST-MODIFIED:20240119T180817Z
UID:4572-1705410000-1705413600@ds.dfci.harvard.edu
SUMMARY:Methods for the Analysis of Data with Missing Values
DESCRIPTION:Frontiers in Biostatistics Seminar \nTuesday January 16\, 2023 @ 1pm ET\nCenter for Life Sciences Building\, Room 11081 \nRoderick Little\, PhD\nRichard D. Remington Distinguished University Professor of Biostatistics\nProfessor\, Department of Statistics\nResearch Professor\, Institute for Social Research\nUniversity of Michigan School of Public Health \nYouTube Video \nAbstract: I review methods for handling missing data in empirical studies. I define missing data\, provide a taxonomy of main approaches to analysis\, including complete-case and available-case analysis\, weighting\, maximum likelihood (ML)\, Bayes\, single and multiple imputation (MI)\, and augmented inverse-probability weighting (AIPW). Assumptions about the missingness mechanism are key to the performance of alternative methods; I define missingness mechanisms\, which play a key role in the performance of methods. Approaches to robust inference\, and to inference when the mechanism is potentially missing not at random\, are discussed. I’ll also discuss recent developments in the treatment of missing data in interventional studies\, as evidenced by the International Council for Harmonization E9 Addendum on estimands. \nWant to get our weekly events newsletter? Click here!
URL:https://ds.dfci.harvard.edu/event/frontiers-in-biostatistics-seminar-roderick-little/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2023/09/rlittle_crop.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240124T120000
DTEND;TZID=America/New_York:20240124T130000
DTSTAMP:20260412T105213
CREATED:20240111T154411Z
LAST-MODIFIED:20240201T125325Z
UID:4827-1706097600-1706101200@ds.dfci.harvard.edu
SUMMARY:Tracing the Mutational Footprints of Cancer to Guide Personalized Therapy
DESCRIPTION:Elevate @ Eleven: Comp Bio Connections \nWednesday January 24th\, 2023\n12:00-1:00PM\nIn-person only\, Zelen Commons\, 11th floor of the Center for Life Sciences Building \nDoğa Gülhan\, Principal Investigator\, Mass General Cancer Center\, KF-CCR \nLunch is provided.
URL:https://ds.dfci.harvard.edu/event/tracing-the-mutational-footprints-of-cancer-to-guide-personalized-therapy/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2024/01/gulhan-square.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240131T130000
DTEND;TZID=America/New_York:20240131T173000
DTSTAMP:20260412T105213
CREATED:20240104T204924Z
LAST-MODIFIED:20240104T204924Z
UID:4782-1706706000-1706722200@ds.dfci.harvard.edu
SUMMARY:DF/HCC Celebration of Early Career Investigators in Cancer Research
DESCRIPTION:Wednesday January 31\, 2024\n1:00pm – 5:30PM\nYawkey Conference Center\, Dana-Farber Cancer Institute\nRegistration. \n2024 Keynote Speaker: Jeff Leek\, PhD\nChief Data Officer\, Vice President\, and J Orin Edson Foundation Chair of Biostatistics at the Fred Hutchinson Cancer Center\nTalk Title: “Taking Calculated Career Risks to Impact the World Through Data Science” \nIntroductions by: \n\nRamesh Shivdasani\, Deputy Director of the DF/HCC and Professor of Medicine at Harvard Medical School\, and\nLaurie Glimcher\, Director of the DF/HCC and President and CEO of the Dana-Farber Cancer Institute\n\nEarly career investigators are a unique reservoir of new ideas\, innovation\, and excellence in cancer research. To celebrate this\, we welcome you to join the 11th Annual DF/HCC Celebration of Early Investigators in Cancer Research. This symposium will showcase the talent of early career investigators at the Dana-Farber/Harvard Cancer Center (DF/HCC) who work in several areas of population science\, including epidemiology\, biostatistics\, outcomes\, diversity\, and survivorship. We invite all members of the public to attend the event. We also invite students\, post-docs\, residents\, clinical fellows\, and early career investigators to submit abstracts for consideration as oral or poster presentations. We look forward to an exciting afternoon of discussion\, sharing new discoveries\, and building new collaborations. – Lorelei Mucci\, ScD (HSPH)\, Giovanni Parmigiani\, PhD (DFCI)\, Erica Feick (DFCI)\, Bailey Vaselkiv (HSPH)\, and Hannah Guard (HSPH). \nCurrently\, the event will be broadcast live without any recording option. All speakers must attend in person. Adjustments to the event status will be considered if there are changes to masking regulations.
URL:https://ds.dfci.harvard.edu/event/df-hcc-celebration-of-early-career-investigators-in-cancer-research/
CATEGORIES:Symposium
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2024/01/logo-only-e1704401329917.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240206T130000
DTEND;TZID=America/New_York:20240206T140000
DTSTAMP:20260412T105213
CREATED:20240126T132133Z
LAST-MODIFIED:20240209T201454Z
UID:4874-1707224400-1707228000@ds.dfci.harvard.edu
SUMMARY:Quantitative Methods in Implementation Research: Concepts\, Goals\, and Applications
DESCRIPTION:Frontiers in Biostatistics Seminar \nTuesday February 6\, 2024 @ 1pm ET\nCenter for Life Sciences Building\, Room 11081 \nYou Tube Link \nDonna Spiegelman\, ScD\nSusan Dwight Bliss Professor of Biostatistics and Professor of Cardiovascular Medicine\, Yale School of Medicine Professor\, Department of Statistics and Data Science\, Yale University \nThis talk will provide an overview of the key concepts and goals of quantitative methods that are popular in implementation research\, with a wide range of real-world applications. Randomized\, quasi-experimental and observational designs will be covered.
URL:https://ds.dfci.harvard.edu/event/frontiers-in-biostatistics-donna-spiegelman/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2024/01/spiegelman-crop.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240207T120000
DTEND;TZID=America/New_York:20240207T130000
DTSTAMP:20260412T105213
CREATED:20240129T134117Z
LAST-MODIFIED:20240209T142125Z
UID:4891-1707307200-1707310800@ds.dfci.harvard.edu
SUMMARY:Reconstructing the Chronology of Somatic Events From Precursor Conditions to Advanced Stage Myeloma
DESCRIPTION:Elevate @ Eleven: Comp Bio Connections \nWednesday February 7th\, 2024\n12:00-1:00PM\nIn-person only\, Zelen Commons\, 11th floor of the Center for Life Sciences Building \nMehmet Samur\, Senior Research Scientist\, Department of Data Science \nLunch is provided.
URL:https://ds.dfci.harvard.edu/event/reconstructing-the-chronology-of-somatic-events-from-precursor-conditions-to-advanced-stage-myeloma/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2020/04/samur_mehmet.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20240301
DTEND;VALUE=DATE:20240302
DTSTAMP:20260412T105213
CREATED:20240209T142504Z
LAST-MODIFIED:20240304T124147Z
UID:4928-1709251200-1709337599@ds.dfci.harvard.edu
SUMMARY:Call for Abstracts: Health Disparities and Cancer
DESCRIPTION:We invite students\, postdocs\, residents\, clinical fellows\, and early career faculty to submit abstracts for consideration as a lightning talk at the 2024 Marvin Zelen Memorial Symposium. Submit via this form by Friday March 1st\, speakers will be notified by Friday March 8th. \n  \nFriday April 5\, 2024\n1:00-5:30PM ET \nYawkey Conference Center\n450 Brookline Ave\, Boston\, MA \nRegistration for in person and virtual attendance. \nInvited speakers: \n\nAdewole Adamson\, MD\, MPP\, Dell Medical School at the University of Texas at Austin\nCynthia Dwork\,PhD\, Harvard University\nNate Fillmore\,PhD\, VA Boston Healthcare System and Harvard Medical School\nCarmen E. Guerra\, MD\, MSCE\, University of Pennsylvania\nJinani Jayasekera\, PhD\, National Institute on Minority Health and Health Disparities\nBogdan Pasaniuc\,PhD\, University of California Los Angeles\n\n 
URL:https://ds.dfci.harvard.edu/event/call-for-abstracts-health-disparities-and-cancer/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2024/02/Zelen2024_forwebsite_image.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240312T130000
DTEND;TZID=America/New_York:20240312T140000
DTSTAMP:20260412T105213
CREATED:20240104T203211Z
LAST-MODIFIED:20240311T185258Z
UID:4778-1710248400-1710252000@ds.dfci.harvard.edu
SUMMARY:Frontiers in Biostatistics: A Framework for Personalizing the Timing of Surveillance Testing
DESCRIPTION:**This seminar has been canceled. A new date will be announced shortly**\nFrontiers in Biostatistics Seminar \nTuesday March 12\, 2024 @ 1pm ET \n  \nAasthaa Bansal\, PhD\nAssociate Professor\, The Comparative Health Outcomes\, Policy\, and Economics (CHOICE) Institute\, University of Washington\nJoint Associate Professor\, Public Health Sciences Division\nJoint Associate Professor\, Hutchinson Institute for Cancer Outcomes Research (HICOR)\nFred Hutch Cancer Center \nAbstract: Frequent surveillance testing using biomarkers is recommended and routinely conducted in several disease settings. Although surveillance tests provide information about current disease status and present an opportunity to detect disease progression early\, the complications and costs of frequent tests may not be justified for patients who are at low risk of progression. I will discuss our recently developed Personalized Risk-Adaptive Surveillance (PRAISE) framework\, a method for embedding dynamic predictions into a sequential decision-making framework to determine the time point at which the next collection of biomarker data would be most valuable. I will demonstrate a preliminary application of the framework in cystic fibrosis and ongoing work in colorectal cancer to develop more cost-effective and personalized surveillance strategies.
URL:https://ds.dfci.harvard.edu/event/frontiers-in-biostatistics-aasthaa-bansal/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2024/01/aasthaa_headshot_square-scaled-e1708014759804.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240405T130000
DTEND;TZID=America/New_York:20240405T170000
DTSTAMP:20260412T105213
CREATED:20240205T132216Z
LAST-MODIFIED:20240409T122906Z
UID:4900-1712322000-1712336400@ds.dfci.harvard.edu
SUMMARY:2024 Marvin Zelen Symposium: Health Disparities and Cancer
DESCRIPTION:Friday April 5\, 2024\n1:00-5:00PM ET \nYawkey Conference Center\n450 Brookline Ave\, Boston\, MA\nIn-person event only\, the recording will be available post-event. \nRegistration for in person attendance. \nInvited speakers: \n\nAdewole Adamson\, MD\, MPP\, Dell Medical School at the University of Texas at Austin\, “AI and Melanoma Disparities”\nCynthia Dwork\,PhD\, Harvard University\, “Individuals\, Groups\, Indistinguishability\, and Loss: 15 Years of Algorithmic Fairness in 20 Minutes”\nNate Fillmore\,PhD\, VA Boston Healthcare System and Harvard Medical School\, “Health Disparities and Cancer in the National VA Healthcare System”\nCarmen E. Guerra\, MD\, MSCE\, University of Pennsylvania\, “The (Mis)use of Race and Ethnicity in Biomedical Research”\nJinani Jayasekera\, PhD\, National Institute on Minority Health and Health Disparities\, “Personalized Clinical Decision Tools to Support Equitable Breast Cancer Care”\nBogdan Pasaniuc\,PhD\, University of California Los Angeles\, “Polygenic risk scoring in personalized medicine: promises and challenges”
URL:https://ds.dfci.harvard.edu/event/2024-marvin-zelen-symposium-health-disparities-and-cancer/
LOCATION:Dana-Farber Cancer Institute\, 450 Brookline Ave\, Boston\, MA\, 02215\, United States
CATEGORIES:Symposium
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2024/02/Zelen2024_forwebsite_image.png
GEO:42.3372552;-71.1076591
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Dana-Farber Cancer Institute 450 Brookline Ave Boston MA 02215 United States;X-APPLE-RADIUS=500;X-TITLE=450 Brookline Ave:geo:-71.1076591,42.3372552
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240411T160000
DTEND;TZID=America/New_York:20240411T170000
DTSTAMP:20260412T105213
CREATED:20240311T124600Z
LAST-MODIFIED:20240415T133053Z
UID:5053-1712851200-1712854800@ds.dfci.harvard.edu
SUMMARY:Data Integration in Statistical Inference and Risk Prediction
DESCRIPTION:Joint Seminar with Harvard TH Chan School of Public Health \nThursday April 11\, 2024 @ 4pm ET\nFXB Building Room 301 \nYu Shen PhD\nConversation with a Living Legend Professor & Chair ad interim\nDepartment of Biostatistics\nThe University of Texas MD Anderson Cancer Center \nIn comparative effectiveness research and risk prediction for rare types of cancer\, it is desirable to combine multiple sources of data\, e.g.\, the primary cohort data together with aggregate information derived from cancer registry databases. Such integration of data may improve statistical efficiency and accuracy of risk prediction\, but also pose statistical challenges for incomparability between different sources of data. We develop the adaptive estimation procedures\, which used the combined information to determine the degree of information borrowing from the aggregate data of the external resource. We apply the proposed methods to evaluate the long-term effect of several commonly used treatments for inflammatory breast cancer by tumor subtypes\, while combining the inflammatory breast cancer patient cohort at MD Anderson and external data.
URL:https://ds.dfci.harvard.edu/event/data-integration-in-statistical-inference-and-risk-prediction/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2024/03/yushen-crop.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240417T120000
DTEND;TZID=America/New_York:20240417T130000
DTSTAMP:20260412T105213
CREATED:20240415T133033Z
LAST-MODIFIED:20240423T144756Z
UID:5314-1713355200-1713358800@ds.dfci.harvard.edu
SUMMARY:Deconvolving Clonotype from High-Throughput Perturb-Seq and Novel Splice Identification of Prematurely Terminated mRNA
DESCRIPTION:Elevate @ Eleven CompBio Connections \nWednesday April 17th\, 2024\n12:00 – 1:00 PM\nZelen Commons\, Center for Life Sciences Building \nJared Brown\, PhD\, Research Fellow\, Data Science \n  \nLunch is provided.
URL:https://ds.dfci.harvard.edu/event/deconvolving-clonotype-from-high-throughput-perturb-seq-and-novel-splice-identification-of-prematurely-terminated-mrna/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2021/08/Brown_Jared.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240501T120000
DTEND;TZID=America/New_York:20240501T130000
DTSTAMP:20260412T105213
CREATED:20240415T145532Z
LAST-MODIFIED:20240502T125348Z
UID:5322-1714564800-1714568400@ds.dfci.harvard.edu
SUMMARY:Identifying Transcription Factor Binding using Open Chromatin\, Transcriptome\, and Methylation Data
DESCRIPTION:Elevate @ Eleven CompBio Connections \nWednesday May 1st\, 2024\n12:00 – 1:00 PM\nZelen Commons\, Center for Life Sciences Building \nMichael Hoffman\, PhD\, Senior Scientist and Chair\, Princess Margaret Cancer Centre and Associate Professor\, University of Toronto \nLunch is provided.
URL:https://ds.dfci.harvard.edu/event/identifying-transcription-factor-binding-using-open-chromatin-transcriptome-and-methylation-data/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2024/04/Hoffman_IMG_3344-cropped-1024x1024-1-e1713192907447.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240507T130000
DTEND;TZID=America/New_York:20240507T140000
DTSTAMP:20260412T105213
CREATED:20240304T124913Z
LAST-MODIFIED:20240507T191511Z
UID:5006-1715086800-1715090400@ds.dfci.harvard.edu
SUMMARY:Cancer Risk Prediction\, Early Detection and Minimal Residual Disease
DESCRIPTION:Frontiers in Biostatistics Seminar \nTuesday May 7\, 2024 @ 1pm ET \nIn-person and Zoom available. \nCristian Tomasetti\, Ph.D.\nDirector\, Center for Cancer Prevention and Early Detection\, City of Hope\nProfessor and Director\, Division of Mathematics for Cancer Evolution and Early Detection\, Department of Computational & Quantitative Medicine\, City of Hope
URL:https://ds.dfci.harvard.edu/event/frontiers-in-biostatistics-cristian-tomasetti/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2024/03/tomasetti-300x300-1-e1709556955216.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240529T120000
DTEND;TZID=America/New_York:20240529T153000
DTSTAMP:20260412T105213
CREATED:20240501T111032Z
LAST-MODIFIED:20240530T171723Z
UID:5353-1716984000-1716996600@ds.dfci.harvard.edu
SUMMARY:Artificial Intelligence Methods in Cancer
DESCRIPTION:DF/HCC Cancer Data Sciences Lunch Workshop \nStep into the future of oncology where our speakers will discuss the cutting-edge intersection of AI and cancer research. This workshop is geared towards researchers and clinicians who are eager to delve into the innovative methodologies that AI brings to the battle against cancer. Join us\, learn\, and contribute to a future where AI and human ingenuity converge to save lives. \nSponsored by the Cancer Data Sciences Program at the Dana-Farber Harvard Cancer Center and the Harvard Chan Bioinformatics Core. \nSpeakers: \n\nJason M. Johnson\, PhD\, Senior Vice President\, Chief Data and Analytics Officer\, Dana-Farber Cancer Institute\nWilliam Lotter\, PhD Assistant Professor\, Harvard Medical School and Dana-Farber Cancer Institute\nMichael Rosenthal\, MD\, PhD Investigator\, Hale Family Center For Pancreatic Cancer Research\, Dana-Farber Cancer Institute\, Assistant Professor\, Harvard Medical School\nCaroline Uhler\, Full Professor\, Department of Electrical Engineering and Computer Science and Institute for Data\, Systems and Society\, Massachusetts Institute of Technology\nEliezer Van Allen\, MD Associate Professor\, Harvard Medical School\, Chief of the Division of Population Sciences\, Dana-Farber Cancer Institute\nKun-Hsing Yu\, MD\, PhD Assistant Professor of Biomedical Informatics Harvard Medical School\n\nRegister for this hybrid event by May 24. 
URL:https://ds.dfci.harvard.edu/event/artificial-intelligence-methods-in-cancer/
CATEGORIES:Workshop
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2024/05/DFHCC-Cancer-Data-Sciences-Workshop-Instagram-Post-e1714561678632.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240724T080000
DTEND;TZID=America/New_York:20240726T170000
DTSTAMP:20260412T105213
CREATED:20240530T171710Z
LAST-MODIFIED:20240729T122914Z
UID:5403-1721808000-1722013200@ds.dfci.harvard.edu
SUMMARY:Bioconductor Conference 2024: Where Software and Biology Meet
DESCRIPTION:July 24-26\, 2024\nVan Andel Institute\nGrand Rapids\, Michigan USA\nRegistration open now!\nWelcome to BioC2024 – Your Bioinformatics Community Awaits \nQuick Reasons to Join Us \n\nFor Everyone in Bioinformatics: Whether you’re deep in research or just starting out\, BioC2024 has something for you. Connect\, learn\, and share in a space that welcomes every level of curiosity and expertise.\nConnect Across the Globe: With our Hopin platform\, you’re not just attending a conference; you’re joining a worldwide community ready to exchange ideas and forge new collaborations.\nLearn From the Best: Our lineup includes some of the most forward-thinking minds in bioinformatics. Expect insights that could change how you see your work or study.\nDiversity Drives Us: We’re proud to host a diverse and inclusive event. Your unique perspective enriches our community\, and we strive to make BioC2024 accessible to all.\n\nWhat’s in Store \n\nTalks That Inspire: From quick insights to deep dives\, our sessions are designed to spark new ideas and provide practical knowledge.\nHands-On Experience: Enhance your skill set with workshops and demos that put theory into practice. It’s learning made relevant\, regardless of your experience level.\nShaped by You: Your feedback has been our guide. Expect more interactive opportunities\, a broader range of topics\, and even better virtual engagement.\n\nJoin the BioC2024 Experience \nBioC2024 is more than a conference – it’s a chance to grow\, connect\, and contribute to the bioinformatics field. Don’t miss out. Secure your spot now and be ready to be inspired.
URL:https://ds.dfci.harvard.edu/event/bioconductor-conference-2024-where-software-and-biology-meet/
CATEGORIES:Conference
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240813T130000
DTEND;TZID=America/New_York:20240813T140000
DTSTAMP:20260412T105213
CREATED:20240806T113832Z
LAST-MODIFIED:20240815T144154Z
UID:5477-1723554000-1723557600@ds.dfci.harvard.edu
SUMMARY:Challenges of Producing High-Quality Labelled Data
DESCRIPTION:Tuesday\, August 13 @ 1:00PM Eastern Time\nCenter for Life Sciences Building\, 11th floor\, room 11081\n3 Blackfan Circle\, Boston \nPeter Lipman\nTechnical Lead & Manager\nData Science & Human Computation\, Google \nZoom: https://bit.ly/plipman
URL:https://ds.dfci.harvard.edu/event/challenges-of-producing-high-quality-labelled-data/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2024/08/lipman_headshot_crop.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240830T080000
DTEND;TZID=America/New_York:20240830T170000
DTSTAMP:20260412T105213
CREATED:20240729T122857Z
LAST-MODIFIED:20240904T112937Z
UID:5455-1725004800-1725037200@ds.dfci.harvard.edu
SUMMARY:Fall schedule to be announced
DESCRIPTION:Watch here for updates on our fall seminar schedule. You can also sign up for our weekly newsletter to stay informed of data science events in the Boston area.
URL:https://ds.dfci.harvard.edu/event/fall-schedule-to-be-announced/
CATEGORIES:Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240912T160000
DTEND;TZID=America/New_York:20240912T170000
DTSTAMP:20260412T105213
CREATED:20240904T112923Z
LAST-MODIFIED:20240917T172028Z
UID:5503-1726156800-1726160400@ds.dfci.harvard.edu
SUMMARY:Hierarchical Causal Models
DESCRIPTION:HSPH Biostatistics and DFCI Data Science Colloquium Series \nThursday September 12\, 2024\n4:00-5:00PM\nHSPH FXB Building Room 301 \nDavid Blei\, PhD\nProfessor of Statistics and Computer Science\nColumbia University \nAnalyzing nested data with hierarchical models is a staple of Bayesian statistics\, but causal modeling remains largely focused on “flat” models. In this talk\, we will explore how to think about nested data in causal models\, and we will consider the advantages of nested data over aggregate data (such as data means) for causal inference. We show that disaggregating your data—replacing a flat causal model with a hierarchical causal model—can provide new opportunities for identification and estimation. \nAs examples\, we will study how to identify and estimate causal effects under unmeasured confounders\, interference\, and instruments. \nThis is joint work with Eli Weinstein.
URL:https://ds.dfci.harvard.edu/event/hierarchical-causal-models/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ds.dfci.harvard.edu/wp-content/uploads/2024/09/blei_headshot_crop.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240919T160000
DTEND;TZID=America/New_York:20240919T170000
DTSTAMP:20260412T105213
CREATED:20240917T172017Z
LAST-MODIFIED:20240920T175443Z
UID:5541-1726761600-1726765200@ds.dfci.harvard.edu
SUMMARY:Inference for Treatment-Specific Survival Curves using Machine Learning
DESCRIPTION:HSPH Biostatistics and DFCI Data Science Colloquium Series \nThursday September 19\, 2024\n4:00-5:00PM\nHSPH FXB Building Room 313 \nTed Westling\, Assistant Professor\, Department of Mathematics & Statistics\, University of Massachusetts Amherst \nIn the absence of data from a randomized trial\, researchers often aim to use observational data to draw causal inference about the effect of a treatment on a time-to-event outcome. In this context\, interest often focuses on the treatment-specific survival curves; that is\, the survival curves were the entire population under study to be assigned to receive the treatment or not. Under certain causal conditions\, including that all confounders of the treatment-outcome relationship are observed\, the treatment-specific survival can be identified with a covariate-adjusted survival function. Several estimators of this function have been proposed\, including estimators based on outcome regression\, inverse probability weighting\, and doubly robust estimators. We propose a cross-fitted doubly-robust estimator that incorporates data-adaptive estimators of the conditional survival functions. We establish conditions on the nuisance estimators under which our estimator is consistent and asymptotically linear\, both pointwise and uniformly in time. We also propose an ensemble learner for combining multiple candidate estimators of the conditional survival estimators. Our methods and results accommodate events occurring in discrete or continuous time (or both). We investigate the practical performance of our methods using an application to the effect of a surgical treatment to prevent metastases of parotid carcinoma on mortality. Time permitting\, we will discuss ongoing work concerning sensitivity analysis for survival curves.
URL:https://ds.dfci.harvard.edu/event/inference-for-treatment-specific-survival-curves-using-machine-learning/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2024/09/Ted-Westling-long.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241011T160000
DTEND;TZID=America/New_York:20241011T170000
DTSTAMP:20260412T105213
CREATED:20240920T175432Z
LAST-MODIFIED:20241008T113541Z
UID:5562-1728662400-1728666000@ds.dfci.harvard.edu
SUMMARY:Call for abstracts: DF/HCC Celebration of Early Career Investigators
DESCRIPTION:The Dana-Farber/Harvard Cancer Center will be holding its annual Celebration of Early Career Investigators on December 3rd\, 2024 from 1:00 – 5:00 PM in-person at the Dana-Farber Cancer Institute. \nWe encourage students\, postdocs\, residents\, clinical fellows\, and instructors to submit abstracts for consideration as a short talk or as part of the PATHFINDER sponsored poster presentation by October 11th. \n\nTo submit an abstract\, please visit: https://bit.ly/ECIS2024Abstract\nTo register to attend the event\, please visit: https://bit.ly/ECIS2024\nFor more information\, please visit our event website.
URL:https://ds.dfci.harvard.edu/event/call-for-abstracts-df-hcc-celebration-of-early-career-investigators/
CATEGORIES:Symposium
ATTACH;FMTTYPE=image/png:https://ds.dfci.harvard.edu/wp-content/uploads/2024/01/logo-only-e1704401329917.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20241018T150000
DTEND;TZID=America/New_York:20241018T160000
DTSTAMP:20260412T105213
CREATED:20241008T113529Z
LAST-MODIFIED:20241022T164100Z
UID:5585-1729263600-1729267200@ds.dfci.harvard.edu
SUMMARY:Empirical Bayes Matrix Factorization\, and Genomic Applications
DESCRIPTION:Data Science Seminar\nFriday\, October 18\, 3:00 PM ET \nCenter for Life Sciences Building\, 11th Floor \nMatthew Stephens\, PhD\nChair\, Department of Statistics; Ralph W. Gerard Professor of Statistics\, Human Genetics\, University of Chicago
URL:https://ds.dfci.harvard.edu/event/empirical-bayes-matrix-factorization-and-genomic-applications/
CATEGORIES:Seminar
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END:VEVENT
END:VCALENDAR