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NIH launched the Long COVID Computational Challenge, which will award up to $500k in support of data-driven solutions that help us understand the risks of developing the condition. The primary objective of the Long COVID Computational Challenge (L3C) is to focus on the prognostic problem by developing AI/ML models and algorithms that serve as open-source tools for using structured medical records to identify which patients infected with SARS-CoV-2 have a high likelihood of developing PASC/Long…

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The NCI Center for Biomedical Informatics and Information Technology (CBIIT) training program invites you to attend an upcoming webinar on Informatics Technology for Cancer Research (ITCR) and scientific software trainings. On Thursday, December 8, 2022, 10:00-11:00 a.m. ET, attend Advanced Ingenuity Pathway Analysis by Qiagen featuring speaker Shawn Price, Field Application Scientist. Learn how to leverage Activity Plot, Pattern Search, Comparison Analysis, Analysis Match, and Land…

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The NCI Center for Biomedical Informatics and Information Technology (CBIIT) training program invites you to attend an upcoming webinar on Informatics Technology for Cancer Research (ITCR) and scientific software trainings. On Thursday, December 8, 2022, 10:00-11:00 a.m. ET, attend Advanced Ingenuity Pathway Analysis by Qiagen featuring speaker Shawn Price, Field Application Scientist. Learn how to leverage Activity Plot, Pattern Search, Comparison Analysis, Analysis Match, and Land Explorer. To register.

NIH launched the Long COVID Computational Challenge, which will award up to $500k in support of data-driven solutions that help us understand the risks of developing the condition. The primary objective of the Long COVID Computational Challenge (L3C) is to focus on the prognostic problem by developing AI/ML models and algorithms that serve as open-source tools for using structured medical records to identify which patients infected with SARS-CoV-2 have a high likelihood of developing PASC/Long COVID. For more information: https://www.imagwiki.nibib.nih.gov/news-events/announcements/announcing-nih-long-covid-computational-challenge-l3c.

The Virtual Digital Twin Micro Lab was held on April 23, 2020 with participants from more than 40 organizations. Download the video presentations, see the PowerPoint slides and read the breakout discussion notes!

Registration is now open for the 2019 ML-MSM Meeting (October 24-25, 2019) to be held in Bethesda, MD (NIH Campus). The meeting will focus on multiple domain approaches to developing Digital Twins and addressing Human Safety.

Paul Macklin of Indiana University – and MicroLab co-lead of Digital Twin ― co-authored a paper with Argonne National Lab (which includes running many patient simulations on HPC to screen treatment choices). The paper is titled, “Learning-accelerated discovery of immune-tumour interactions,” published in Molecular Systems Design and Engineering on June 7, 2019.