Skip to main content

Frederick National Laboratory for Cancer Research issued a request for proposal. To further advance AI in Medical Imaging (AIMI) large datasets, acquired through routine standard of care, are needed to train and evaluate the performance of the ML/AI algorithms. The datasets need to be correctly de-identified to maintain patient privacy while at the same time preserving as much scientifically relevant information as possible. Large datasets from the existing standard of care radiology…

More...

Close

U.S. Department of Energy’s INCITE program seeks proposals for 2023: https://www.doeleadershipcomputing.org/. INCITE’s open call provides an opportunity for researchers to pursue transformational advances in science and technology through large allocations of computer time and supporting resources at the Argonne Leadership Computing Facility (ALCF) and the Oak Ridge Leadership Computing Facility (OLCF). Both are DOE Office of Science user facilities located at DOE’s Argonne…

More...

Close

Workshop Series

In March 2021, Four Interactive, Multidisciplinary Workshops + a World Café* were held to help shape a “Blue-Sky” vision for the future of Radiation Oncology:

March 10, 2021, The Biological Machinery for Advancing Radiation Oncology: Mechanisms, Systems and Simulations (Topic Hosts: Michael Espey, PhD, and Cynthia Keppel, MSc, PhD)

March 12, 2021, The Frontiers of Computational Modeling and Simulations in Multiscale Radiation Oncology (Topic Hosts: Nathan Moore, PhD, and Matthew Coleman, PhD)

March 18, 2021, Learning from Care Delivery: The How and Why of Multi-omics, Biomarkers and Prediction for Radiation Oncology (Topic Hosts: Maximilian Diehn, MD, PhD, and Greeshma Agasthya, PhD)

March 19, 2021, Multimodal Patient Trajectories: Individual Predictive Modeling (Topic Hosts: David Jaffray, PhD; Christopher Hartshorn, PhD; and Georgia Tourassi, PhD)

March 29, 2021, World Café-style* Workshop – Fusion of the Half-day Workshops Culminating in a Directional Whitepaper on The Future of Data and Computing-Enabled Radiation Oncolog

Watch the event Kickoff Video to hear from global experts in Artificial Intelligence, Computing & Radiation. 

Speakers Included:

Purpose of the Workshop Series

Explore emerging and futuristic opportunities among DOE, NCI, and partner institutions to advance radiation therapy. Essential components include:

  • Personalized, adaptive, improved treatment through understanding and development of mechanism-based, computationally enabled modeling
  • Advanced computing to achieve dynamic, multiscale, data-informed, clinically actionable predictions and decision making

Anticipated Outcomes

  • Creation of scope and goals for potential new NCI-DOE Collaboration projects
  • Development of a multi-institutional report with a visionary perspective
  • Opportunities to engage and collaborate with cross-domain researchers and clinicians

This workshop series offered an opportunity to determine a roadmap for cutting-edge, multidisciplinary research that will drive the development of new paradigms in radiation oncology.

Who attended?

  • U.S. and international researchers and clinicians at all levels of seniority with diverse expertise across the continuum of cancer research, radiology, artificial intelligence, scientific computing, data science, biomedical engineering, bioinformatics, physics, and mathematical modeling—including mechanistic, data-driven, and multi-scale modeling
  • People who are passionate about accelerating cancer research and excited about exploring how emerging technology can advance radiation oncology and precision cancer medicine

* A World Café is a discussion format for a challenge or vision that calls for a broad range of disciplines (or diverse set of stakeholders) to all contribute to a vision or plan. A World Café groups each of these stakeholder groups or disciplines together, and then rotates the topic moderators around to each group to consult with each group, developing the vision or plan in an iterative fashion.

Questions? Contact ECICC_Community@nih.gov

Created by Petrina Hollingsworth Last Modified Tue April 26, 2022 8:02 pm by Lynn Borkon