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pankajrajdeo/MRDEF_UMLS

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Hugging Face2024-07-18 更新2024-06-29 收录
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https://hf-mirror.com/datasets/pankajrajdeo/MRDEF_UMLS
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资源简介:
MRDEF数据集是UMLS(统一医学语言系统)元数据的一部分,提供了医学概念和属性的定义。该数据集包含多个特征列,如CUI(概念唯一标识符)、AUI(原子唯一标识符)、ATUI(属性唯一标识符)等,每个列都有详细的描述和示例值。数据集的主要用途是支持医学信息学应用、临床决策支持系统和其他健康相关软件解决方案。

The MRDEF data is a component of the UMLS (Unified Medical Language System) Metathesaurus, available in the Rich Release Format (RRF). This dataset contains definitions for medical concepts and attributes, providing a vital resource for understanding medical terminology and relationships. It supports transparency in source vocabulary and facilitates the generation of accurate change sets between versions of the Metathesaurus.
提供机构:
pankajrajdeo
原始信息汇总

Dataset Card for MRDEF Data

Dataset Description

Dataset Summary

The MRDEF data is a component of the UMLS (Unified Medical Language System) Metathesaurus, available in the Rich Release Format (RRF). This dataset contains definitions for medical concepts and attributes, providing a vital resource for understanding medical terminology and relationships. It supports transparency in source vocabulary and facilitates the generation of accurate change sets between versions of the Metathesaurus.

Purpose

The MRDEF dataset serves as an essential element of the UMLS Metathesaurus, offering definitions for medical concepts. It aids developers and researchers in representing the detailed semantics of each source vocabulary, thereby supporting medical informatics applications, clinical decision support systems, and other health-related software solutions.

Column Descriptions

CUI (Concept Unique Identifier)

  • Description: A unique identifier assigned to each concept within the UMLS Metathesaurus.
  • Values: Alphanumeric strings, such as C0001175. Each value uniquely identifies a medical concept.

AUI (Atom Unique Identifier)

  • Description: A unique identifier for an atom, which is a specific occurrence of a string in a source vocabulary.
  • Values: Variable length field, typically 8 or 9 characters, such as A0019180. Each value uniquely identifies an atom within the dataset.

ATUI (Attribute Unique Identifier)

  • Description: A unique identifier for an attribute associated with a concept or atom.
  • Values: Alphanumeric strings, such as AT38139119. Each value uniquely identifies an attribute within the dataset.

SATUI (Source Asserted Attribute Identifier)

  • Description: An optional identifier provided by the source, representing the attribute as asserted by the source vocabulary.
  • Values: Alphanumeric strings, such as AT51221477. This field may be blank if the source does not provide an asserted identifier.

SAB (Source Abbreviation)

  • Description: The abbreviated name of the source from which the definition is derived.
  • Values: Alphanumeric strings with a maximum length of 20 characters, such as MSH, CSP, NCI_NCI-GLOSS. Each value represents an abbreviated source name.

DEF (Definition)

  • Description: The definition of the medical concept or attribute as provided by the source.
  • Values: Text strings that can vary in length, up to approximately 3,000 characters. For example, "An acquired defect of cellular immunity associated with infection by the human immunodeficiency virus (HIV)..."

SUPPRESS (Suppressible Flag)

  • Description: A flag indicating the suppressible status of the attribute. It reflects whether the attribute should be suppressed in certain views or uses.
  • Values: One of the following values - O, E, Y, or N. These values indicate the status of the suppressibility of the attribute, with N typically meaning not suppressible.

Example Record

CUI: C0001175 AUI: A0019180 ATUI: AT38139119 SATUI: (empty) SAB: MSH DEF: An acquired defect of cellular immunity associated with infection by the human immunodeficiency virus (HIV)... SUPPRESS: N

Usage

This dataset is primarily intended for developers and researchers working on medical informatics applications. It can be used to ensure accurate and comprehensive understanding of medical terms and their relationships, support clinical decision-making, and enhance health information systems.

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