2 datasets found
  1. p

    MIMIC-III Clinical Database

    • physionet.org
    Updated Sep 4, 2016
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    Alistair Johnson; Tom Pollard; Roger Mark (2016). MIMIC-III Clinical Database [Dataset]. http://doi.org/10.13026/C2XW26
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    Dataset updated
    Sep 4, 2016
    Authors
    Alistair Johnson; Tom Pollard; Roger Mark
    License

    https://github.com/MIT-LCP/license-and-dua/tree/master/draftshttps://github.com/MIT-LCP/license-and-dua/tree/master/drafts

    Description

    MIMIC-III is a large, freely-available database comprising deidentified health-related data associated with over forty thousand patients who stayed in critical care units of the Beth Israel Deaconess Medical Center between 2001 and 2012. The database includes information such as demographics, vital sign measurements made at the bedside (~1 data point per hour), laboratory test results, procedures, medications, caregiver notes, imaging reports, and mortality (including post-hospital discharge).MIMIC supports a diverse range of analytic studies spanning epidemiology, clinical decision-rule improvement, and electronic tool development. It is notable for three factors: it is freely available to researchers worldwide; it encompasses a diverse and very large population of ICU patients; and it contains highly granular data, including vital signs, laboratory results, and medications.

  2. p

    MIMIC-IV

    • physionet.org
    Updated Oct 11, 2024
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    Alistair Johnson; Lucas Bulgarelli; Tom Pollard; Brian Gow; Benjamin Moody; Steven Horng; Leo Anthony Celi; Roger Mark (2024). MIMIC-IV [Dataset]. http://doi.org/10.13026/kpb9-mt58
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    Dataset updated
    Oct 11, 2024
    Authors
    Alistair Johnson; Lucas Bulgarelli; Tom Pollard; Brian Gow; Benjamin Moody; Steven Horng; Leo Anthony Celi; Roger Mark
    License

    https://github.com/MIT-LCP/license-and-dua/tree/master/draftshttps://github.com/MIT-LCP/license-and-dua/tree/master/drafts

    Description

    Retrospectively collected medical data has the opportunity to improve patient care through knowledge discovery and algorithm development. Broad reuse of medical data is desirable for the greatest public good, but data sharing must be done in a manner which protects patient privacy. Here we present Medical Information Mart for Intensive Care (MIMIC)-IV, a large deidentified dataset of patients admitted to the emergency department or an intensive care unit at the Beth Israel Deaconess Medical Center in Boston, MA. MIMIC-IV contains data for over 65,000 patients admitted to an ICU and over 200,000 patients admitted to the emergency department. MIMIC-IV incorporates contemporary data and adopts a modular approach to data organization, highlighting data provenance and facilitating both individual and combined use of disparate data sources. MIMIC-IV is intended to carry on the success of MIMIC-III and support a broad set of applications within healthcare.

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Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Alistair Johnson; Tom Pollard; Roger Mark (2016). MIMIC-III Clinical Database [Dataset]. http://doi.org/10.13026/C2XW26

MIMIC-III Clinical Database

Explore at:
Dataset updated
Sep 4, 2016
Authors
Alistair Johnson; Tom Pollard; Roger Mark
License

https://github.com/MIT-LCP/license-and-dua/tree/master/draftshttps://github.com/MIT-LCP/license-and-dua/tree/master/drafts

Description

MIMIC-III is a large, freely-available database comprising deidentified health-related data associated with over forty thousand patients who stayed in critical care units of the Beth Israel Deaconess Medical Center between 2001 and 2012. The database includes information such as demographics, vital sign measurements made at the bedside (~1 data point per hour), laboratory test results, procedures, medications, caregiver notes, imaging reports, and mortality (including post-hospital discharge).MIMIC supports a diverse range of analytic studies spanning epidemiology, clinical decision-rule improvement, and electronic tool development. It is notable for three factors: it is freely available to researchers worldwide; it encompasses a diverse and very large population of ICU patients; and it contains highly granular data, including vital signs, laboratory results, and medications.

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