3 datasets found
  1. f

    Table of dataset characteristics used for the benchmark.

    • plos.figshare.com
    xls
    Updated Jun 5, 2023
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    Tobias Johannes Brix; Philipp Bruland; Saad Sarfraz; Jan Ernsting; Philipp Neuhaus; Michael Storck; Justin Doods; Sonja Ständer; Martin Dugas (2023). Table of dataset characteristics used for the benchmark. [Dataset]. http://doi.org/10.1371/journal.pone.0199242.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 5, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Tobias Johannes Brix; Philipp Bruland; Saad Sarfraz; Jan Ernsting; Philipp Neuhaus; Michael Storck; Justin Doods; Sonja Ständer; Martin Dugas
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Table of dataset characteristics used for the benchmark.

  2. f

    Table illustrating the five different categories the application...

    • plos.figshare.com
    xls
    Updated Jun 3, 2023
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    Tobias Johannes Brix; Philipp Bruland; Saad Sarfraz; Jan Ernsting; Philipp Neuhaus; Michael Storck; Justin Doods; Sonja Ständer; Martin Dugas (2023). Table illustrating the five different categories the application distinguishes and their calculated statistics and charts. [Dataset]. http://doi.org/10.1371/journal.pone.0199242.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Tobias Johannes Brix; Philipp Bruland; Saad Sarfraz; Jan Ernsting; Philipp Neuhaus; Michael Storck; Justin Doods; Sonja Ständer; Martin Dugas
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Table illustrating the five different categories the application distinguishes and their calculated statistics and charts.

  3. c

    SDTM datasets of clinical data and measurements for selected cancer...

    • dev.cancerimagingarchive.net
    csv, n/a, xpt
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    The Cancer Imaging Archive, SDTM datasets of clinical data and measurements for selected cancer collections to TCIA [Dataset]. http://doi.org/10.7937/TCIA.2019.zfv154m9
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    n/a, xpt, csvAvailable download formats
    Dataset authored and provided by
    The Cancer Imaging Archive
    License

    https://www.cancerimagingarchive.net/data-usage-policies-and-restrictions/https://www.cancerimagingarchive.net/data-usage-policies-and-restrictions/

    Time period covered
    Jun 21, 2019
    Dataset funded by
    National Cancer Institutehttp://www.cancer.gov/
    Description

    The Data Integration & Imaging Informatics (DI-Cubed) project explored the issue of lack of standardized data capture at the point of data creation, as reflected in the non-image data accompanying 4 TCIA breast cancer collections (Multi-center breast DCE-MRI data and segmentations from patients in the I-SPY 1/ACRIN 6657 trials (ISPY1), BREAST-DIAGNOSIS, Single site breast DCE-MRI data and segmentations from patients undergoing neoadjuvant chemotherapy (Breast-MRI-NACT-Pilot), The Cancer Genome Atlas Breast Invasive Carcinoma Collection (TCGA-BRCA)) and the Ivy Glioblastoma Atlas Project (IvyGAP) brain cancer collection. The work addressed the desire for semantic interoperability between various NCI initiatives by aligning on common clinical metadata elements and supporting use cases that connect clinical, imaging, and genomics data. Accordingly, clinical and measurement data imported into I2B2 were cross-mapped to industry standard concepts for names and values including those derived from BRIDG, CDISC SDTM, DICOM Structured Reporting models and using NCI Thesaurus, SNOMED CT and LOINC controlled terminology. A subset of the standardized data was then exported from I2B2 in SDTM compliant SAS transport files. The SDTM data was derived from data taken from both the curated TCIA spreadsheets as well as tumor measurements and dates from the TCIA Restful API. Due to the nature of the available data not all SDTM conformance rules were applicable or adhered to. These Study Data Tabulation Model format (SDTM) datasets were validated using Pinnacle 21 CDISC validation software. The validation software reviews datasets according to their degree of conformance to rules developed for the purposes of FDA submissions of electronic data. Iterative refinements were made to the datasets based upon group discussions and feedback from the validation tool. Export datasets for the following SDTM domains were generated:

    • DM (Demographics)
    • DS (Disposition)
    • MI (Microscopic Findings)
    • PR (Procedures)
    • SS (Subject Status)
    • TU (Tumor/Lesion Identification)
    • TR (Tumor/Lesion Results)

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Tobias Johannes Brix; Philipp Bruland; Saad Sarfraz; Jan Ernsting; Philipp Neuhaus; Michael Storck; Justin Doods; Sonja Ständer; Martin Dugas (2023). Table of dataset characteristics used for the benchmark. [Dataset]. http://doi.org/10.1371/journal.pone.0199242.t002

Table of dataset characteristics used for the benchmark.

Related Article
Explore at:
xlsAvailable download formats
Dataset updated
Jun 5, 2023
Dataset provided by
PLOS ONE
Authors
Tobias Johannes Brix; Philipp Bruland; Saad Sarfraz; Jan Ernsting; Philipp Neuhaus; Michael Storck; Justin Doods; Sonja Ständer; Martin Dugas
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

Table of dataset characteristics used for the benchmark.

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