describe and explain in details Unified Medical Language System
The Unified Medical Language System (UMLS) is a compendium of many controlled vocabularies in the biomedical sciences (created 1986).[1] It provides a mapping structure among these vocabularies and thus allows one to translate among the various terminology systems; it may also be viewed as a comprehensive thesaurus and ontology of biomedical concepts. UMLS further provides facilities for natural language processing. It is intended to be used mainly by developers of systems in medical informatics.
UMLS consists of Knowledge Sources (databases) and a set of software tools.
The UMLS was designed and is maintained by the US National Library of Medicine, is updated quarterly and may be used for free. The project was initiated in 1986 by Donald A.B. Lindberg, M.D., then Director of the Library of Medicine.
Description
The Metathesaurus
The Metathesaurus contains syntactic and semantic information about medical terms that appear in 38 controlled vocabularies and classifications, such as SNOMED, MeSh, and ICD. It is organised by concept, and contains over 330,000 concepts and 739,439 terms. It also contains syntactic variations of terms, represented as strings. The representation takes the form of three levels: a set of general concepts (represented by a code), a set of concept names (represented by another, related, code) and a set of strings (represented by another code and the lexical string itself). An illustrative example is given in below figure. Meanings and relationships are preserved from the source vocabularies, but some additional information is provided and new relationships between concepts and terms from different sources are established.
The relationships described between concepts in the metathesaurus
are the following:
An example record from the relational file is given below.
C0001430 | CHD | C0022134 | isa | MSH97 | MTH
This indicates that there is an is-a relationship between the concept nesidioblastoma (C0001430) and the term adenoma (C0022134), that the former is a child of the latter, the source of the relationship comes from the MeSh subject headings (MSH97), and that this relationship was created specifically for the Metathesaurus (MTH).
The Semantic Network
The semantic network contains information about the semantic types that are assigned to the concepts in the Metathesaurus. The types are defined explicitly by textual information and implicitly by means of the hierarchies represented. The semantic types are represented as nodes and the relationships between them as links. Relationships are established with the highest level possible. As a result, the classifications are very general rather than explicit ones between individual concepts.
In the semantic network, relations are stated between semantic types. The primary relation is that of hyponymy, but there are also five major categories of non-hierarchical relations:
The following example shows how terms can be decomposed into their various concepts and positioned in the hierarchy.
D-33-- Open Wounds of the Limbs
DD-33620 Open wound of knee without complication 891.0
(T-D9200)(M-14010)(G-C009)(F-01450)
DD-33621 Open wound of knee with complication 891.1
(T-D9200)(M-14010)(G-C008)(F-01450)
The Specialist Lexicon
The specialist lexicon provides detailed syntactic information about biomedical terms and common English words. An individual lexical entry is created for each spelling variant and syntactic category for a word. These are then grouped together to form a unit record for each word, defined in a frame structure consisting of slots and fillers. Full morphological and syntactic information is provided, e.g. syntactic category, number, gender, tense, adjectival type, noun type, etc.
The Information Sources Map
The information sources map contains details of the original sources of the terms. It consists of a database of records describing the information resources, with details such as scope, probability utility and access conditions. The sources themselves are varied and include bibliographic databases, factual databases and expert systems.
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