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NASEM’s report on Digital Twins is now available!

“Foundational Research Gaps & Future Directions for Digital Twins,” published by the National Academies of Sciences, Engineering, and Medicine (NASEM) identifies cross-sector challenges and recommendations to support this potentially transformative approach for biomedical research. Priorities include development of multi-agency collaborations with industry to advance the mathematical, statistical, and computational…

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Request for Information: Calling all Researchers and Healthcare Community Contributors

NEW NCI Childhood Cancer Data Initiative (CCDI) Request for Information (RFI) on Electronic Health Record (EHR) data! Responses due using the submission webform by February 29, 2024.  NCI’s CCDI invites participation from all stakeholders across the cancer research and health care community including vendors and developers in understanding information on existing capabilities for automated EHR…

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Image result for images for cancer analyticsThe Second ECICC Community MicroLab on Cancer Challenges and Advanced Computing was held on September 25, 2019!

  • What is a MicroLab? MicroLabs are 60-90 minute, highly interactive, virtual events. Unlike webinars which are focused on disseminating information, the purpose of MicroLabs is to facilitate stimulating scientific discussions in smaller more intimate virtual breakout groups.

  • A multi-disciplinary group of over 100 clinicians, researchers, and academics in cancer and computational sciences participated in our second virtual, ECICC Community MicroLab on September 25, 2019!

  • Building on the breakout discussions from the first MicroLab held in June 2019, participants developed use cases for real-life situations and then identified what research challenges need to be overcome. The use cases were based on various personae derived from the 4 cancer challenge areas developed at the Envisioning Computational Innovations for Cancer Challenges (ECICC) Scoping Meeting held in March 2019.

 

MicroLab Presentations:

 

Presenters Included (partial list):

  • MicroLab Origins

    • Emily Greenspan, National Cancer Institute

  • Generating Large-Scale Synthetic Data to protect Personally Identifiable Information

    • Nick Anderson, University of California, Davis

    • Bill Richards, Brigham And Women's Hospital / Harvard University

  • Using Machine Learning for Iterative Hypothesis Generation

    • Amber Simpson, Queen’s University 

  • Creating a Cancer Patient “Digital Twin” to optimize personalized treatment decision-making

    • Tina Hernandez-Boussard, Stanford University

    • Paul Macklin, Indiana University

  • Developing Adaptive Cancer Treatments targeting unique tumor characteristics and trajectories

    • John McPherson, University of California, Davis

  • Use Case Demonstration

    • Paul Macklin, Indiana University

 

If you are interested in learning more -- or joining -- this multi-disciplinary community, please contact ECICCcommunity@nih.gov 


 

Created by Malachi Greaves Last Modified Mon April 25, 2022 4:00 pm by Lynn Borkon