# Flagship Dataset of Type 2 Diabetes from the AI-READI Project

Datasheet for Dataset

    creators: &id001
    - affiliation:
        id: AI-READI Consortium
        name: AI-READI Consortium
      principal_investigator: ''
    description: This dataset contains data from 1067 participants that was collected
      between July 19, 2023 and July 31, 2024. Data from multiple modalities are included.
      The data in this dataset contain no protected health information (PHI). Information
      related to the sex and race/ethnicity of the participants as well as medication
      used has also been removed.
    funders: &id002
    - grant:
        grant_number: 1OT2OD032644
        id: 1OT2OD032644
        name: ''
      grantor:
        id: NIH
        name: National Institutes of Health
    id: doi:10.60775/fairhub.2
    issued: '2024-11-08'
    keywords: &id003
    - Diabetes mellitus
    - Machine Learning
    - Artificial Intelligence
    - Electrocardiography
    - Continuous Glucose Monitoring
    - Retinal imaging
    - Eye exam
    resources:
    - acquisition_methods:
      - description: Data was collected from multiple modalities, including 12-lead ECG,
          Holter monitor, smartwatch, REDCap for clinical data, a custom environmental
          sensor, fluorescence lifetime imaging ophthalmoscopy (FLIO), optical coherence
          tomography (OCT), optical coherence tomography angiography (OCTA), retinal photography,
          wearable fitness trackers, and continuous glucose monitoring (CGM) devices.
        was_directly_observed: ''
        was_inferred_derived: ''
        was_reported_by_subjects: ''
        was_validated_verified: ''
      addressing_gaps: []
      anomalies: []
      bytes: 2210033333333
      cleaning_strategies:
      - description: The data in this dataset contain no protected health information
          (PHI). Information related to the sex and race/ethnicity of the participants
          as well as medication used has also been removed.
      collection_mechanisms: []
      collection_timeframes:
      - description: The data was collected between July 19, 2023 and July 31, 2024.
      compression: ''
      confidential_elements: []
      conforms_to:
      - Clinical Dataset Structure (CDS) v0.1.1
      - WaveForm DataBase (WFDB)
      - Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM)
      - Earth Science Data Systems (ESDS)
      - Digital Imaging and Communications in Medicine (DICOM)
      - Open mHealth
      conforms_to_class: ''
      conforms_to_schema: ''
      content_warnings: []
      created_by: []
      created_on: ''
      creators: *id001
      data_collectors: []
      data_protection_impacts: []
      description: This dataset contains data from 1067 participants that was collected
        between July 19, 2023 and July 31, 2024. Data from multiple modalities are included.
        The data in this dataset contain no protected health information (PHI). Information
        related to the sex and race/ethnicity of the participants as well as medication
        used has also been removed.
      dialect: ''
      discouraged_uses:
      - description: Users must agree to use the data only for type 2 diabetes related
          research. Other uses are implicitly discouraged.
      distribution_dates: []
      distribution_formats:
      - description: The dataset is organized into multiple directories by datatype, with
          file formats including WaveForm DataBase (WFDB), CSV (conforming to OMOP CDM),
          Earth Science Data Systems (ESDS), Digital Imaging and Communications in Medicine
          (DICOM), and Open mHealth.
      doi: 10.60775/fairhub.2
      download_url: ''
      encoding: ''
      errata: []
      ethical_reviews: []
      existing_uses:
      - description: As of the document date, the dataset has 12,603 views, has been cited
          by 3 resources, and has had 539 approved access requests.
      extension_mechanism: ''
      external_resources: []
      format: ''
      funders: *id002
      future_use_impacts: []
      hash: ''
      id: doi:10.60775/fairhub.2
      instances:
      - counts: 1067
        data_substrate: ''
        data_topic: ''
        instance_type: participants
        label: ''
        label_description: ''
        missing_information: []
        sampling_strategies: []
      ip_restrictions: ''
      is_deidentified:
        description:
        - The data in this dataset contain no protected health information (PHI). Information
          related to the sex and race/ethnicity of the participants as well as medication
          used has also been removed.
        identifiable_elements_present: false
      is_tabular: ''
      issued: '2024-11-08'
      keywords: *id003
      labeling_strategies: []
      language: ''
      last_updated_on: ''
      license: https://doi.org/10.5281/zenodo.10642459
      license_and_use_terms:
      - description: This work is licensed under a custom license. Accessing the dataset
          requires logging in through a verified ID system, agreeing to use the data only
          for type 2 diabetes related research, and agreeing to the license terms which
          set restrictions and obligations for data usage.
      maintainers: []
      md5: ''
      media_type: ''
      modified_by: []
      other_tasks: []
      page: ''
      path: ''
      preprocessing_strategies:
      - description: Processing of the data was automated + custom.
      publisher: ''
      purposes:
      - response: The Artificial Intelligence Ready and Exploratory Atlas for Diabetes
          Insights (AI-READI) project seeks to create a flagship ethically-sourced dataset
          to enable future generations of artificial intelligence/machine learning (AI/ML)
          research to provide critical insights into type 2 diabetes mellitus (T2DM),
          including salutogenic pathways to return to health.
      raw_sources: []
      regulatory_restrictions: ''
      retention_limit: ''
      sampling_strategies: []
      sensitive_elements:
      - description:
        - The dataset contains health data related to Type 2 Diabetes. It originally contained
          race/ethnicity and sex data which has been removed from the dataset but is available
          in aggregate form.
        sensitive_elements_present: true
      sha256: ''
      status: ''
      subpopulations:
      - distribution:
        - 'Train Split: Hispanic (144), Asian (167), Black (211), White (225). Male (302),
          Female (445). No DM (292), Lifestyle (162), Oral (235), Insulin (58).'
        - 'Val Split: Hispanic (40), Asian (40), Black (40), White (40). Male (80), Female
          (80). No DM (47), Lifestyle (33), Oral (40), Insulin (40).'
        - 'Test Split: Hispanic (40), Asian (40), Black (40), White (40). Male (80), Female
          (80). No DM (41), Lifestyle (39), Oral (36), Insulin (42).'
        - 'Total: Hispanic (224), Asian (247), Black (291), White (305). Male (462), Female
          (605). No DM (380), Lifestyle (234), Oral (311), Insulin (140).'
        identification:
        - Race/ethnicity
        - Sex
        - Diabetes status
        subpopulation_elements_present: true
      subsets: []
      tasks: []
      title: Flagship Dataset of Type 2 Diabetes from the AI-READI Project
      updates:
      - description: The dataset is versioned. Changes between versions are provided in
          a CHANGELOG file. The current version is 2.0.0, and a previous version 1.0.0
          exists.
      use_repository: []
      version: 2.0.0
      version_access:
      - description: Older versions of the dataset are accessible and have their own DOIs.
          Version 1.0.0 is available at doi:10.60775/fairhub.1.
      was_derived_from: ''
    title: Flagship Dataset of Type 2 Diabetes from the AI-READI Project
    version: 2.0.0

Generated on 2025-08-14 19:52:46