Organization
The Diseases Database is based around a collection of concepts related to human medicine. These concepts include diseases, drugs, symptoms, physical signs and abnormal laboratory results. These are referred to as 'items'. There are around 8,000 items within the database.
In order to link items to both each other and external information resources three sets of metadata are modelled within the database.
Firstly, Diseases Database items are assigned various relationships e.g. diabetes mellitus type 2 is asserted "a risk factor for" ischaemic heart disease. More formally the database employs an entity-attribute-value model with items populating both entity and value slots.
Relationships may be read in either direction e.g. the assertion "myocardial infarction {may cause} chest pain" has the corollary "chest pain {may be caused by} myocardial infarction". Such relationships aggregate within the database and allow lists to be retrieved - e.g. a list of items which may cause chest pain, and a list of items which may be caused by myocardial infarction.
Secondly, most Diseases Database items are assigned topic specific hyperlinks to Web resources which include Online Mendelian Inheritance in Man, eMedicine and Wikipedia.
Thirdly, most Diseases Database items are mapped to concepts within the Unified Medical Language System (UMLS). UMLS links enable the display of short text definitions and/or Medical Subject Heading (MeSH) scope notes for the majority of items on the database.
The UMLS map also enables links to and from other medical classifications and terminologies e.g. ICD-9 and SNOMED.
Diseases Database content can thus potentially be accessed directly via coded identifiers from multiple medical coding systems e.g. the SNOMED concept code for Myocardial infarction 22298006 finds the equivalent Diseases Database item http://www.diseasesdatabase.com/code_translate.asp?strCODE=22298006&strSAB=SNOMEDCT as well as a number of other closely related concepts via UMLS supplied relationships.
Read more about this topic: Diseases Database
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