Updates from the Cancer Research Data Commons:
Empowering the Scientific Community to Make New Discoveries
Featured News
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Featured News
The CRDC's New Data Submission Portal
The CRDC has launched a new Data Submission Portal open to NCI and NIH-funded researchers looking to share their data through the NCI’s primary data sharing platform, CRDC. The new Data Submission Portal supports researchers by streamlining two processes: completing a data Submission Request (i.e. inquiring if their study data can be shared through the CRDC), and once approved, completing their Data Submission (i.e. uploading their data files) through a more transparent process.
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Hold the Date: CRDC 2024 Fall Symposium - October 16 & 17
The Cancer Research Data Commons (CRDC) will hold its 2024 Fall Symposium on October 16th and 17th. This is a one-and-a-half-day event highlighting the CRDC’s 10th anniversary, the impact of the CRDC, and future plans. The symposium is open to the public and available for in-person or online participation.
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Recommendations from NCI CRDC AI Data Readiness Challenge Winners
The winners of the recent NCI Cancer Research Data Commons (CRDC) Artificial Intelligence (AI) Data Readiness Challenge presented their findings and recommendations for improving the AI readiness of NCI CRDC data. Access a recording of the webinar.Recommendations from the winners include, among others:
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Vaidhyanathan Mahaganapathy, Ph.D., Reflects on Support Received from NCI Cloud Resources
Vaidhyanathan (Vaidhy) Mahaganapathy, Ph.D., is a Computational Biologist focused on genomics research for the Applied AI team at the Ellison Institute of Technology (EIT). He recently spoke with CRDC Insights, reflecting on the support he received during his dissertation research from the team at Seven Bridges-Cancer Genomic Cloud (SB-CGC), powered by Velsera.
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The National Cancer Institute (NCI) Medical Image De-Identification Benchmark Challenge (MIDI-B) – Registration is Open
Registration is open through August 15th for the MIDI-B Challenge – the NCI Medical Image De-Identification Benchmark Challenge. This is for developers (independent, academic, or industrial) who want to assess their automated image de-identification algorithms and software tools’ performance against a dataset of DICOM (Digital Imaging and Communications in Medicine) images that will be made available to challenge participants.
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