ICT for Health Care and Life Sciences

Transcription

1 School of Information Engineering Laurea Magistrale in Information Engineering Dipartimento di Elettronica e Informazione ICT for Health Care and Life Sciences 7 th November 2012 Davide Chicco davide.chicco@gmail.com

2 Nettab 2012 Conference in Como next week Nettab 2012 Integrated Bio Search International Conference on Bioinformatics Data Integration FREE FOR POLIMI STUDENTS Wednesday 14 Friday 16 November 2012 Politecnico di Milano Como, Italy, EU

3 ICT for Health Care and Life Sciences UMLS Unified Medical Language System an introduction

4 Motivation In general Purposes Access Licence agreement Knowledge sources Metathesaurus, oveview Semantic Network, overview SPECIALIST Lexicon, overview Metathesaurus in general organization uses example source Semantic Network in general types categories usefulness SPECIALIST Lexicon morphology ortography syntax Lexical tools Wordind Lexical Variant Generation NORM UMLS Terminology Services (UTS) Querying the UTS Further readings on UMLS

5 Motivation Numerous different controlled vocabularies exist especially in the biomedical domain: ICD-9, ICD-10, ICD-9-CM, CPT, HCPCS, LOINC NDC, SNOMED, SNOMED III, SNOMED-RT READ, SNOMED-CT, MeSH, MedDRA, NCI Thesaurus Problems: Ambiguity Which names correspond to the same concept?

6 Motivation (2) Such medical and clinical terminologies were created in different times by different associations for different purposes, but: Some concepts they define are the same Often different controlled terms are used in each terminology to define the same (or similar) concept For data and knowledge description, integration and interoperability matching are required: Matching textual descriptions (even controlled) is difficult The Unified Medical Language System (UMLS) was created and is maintained as a support for integration of biomedical textual annotations scattered in distinct databanks

7 In general UMLS is a compendium of many controlled vocabularies in the biomedical sciences: Provides a mapping structure among these vocabularies Allows to translate a term among the various terminology systems May also be viewed as a comprehensive thesaurus and ontology of biomedical concepts

8 In general (2) The UMLS was designed and is maintained by the US National Library of Medicine, is updated quarterly and may be used for free.

9 In general (3) Started in 1986 By United States National Library of Medicine, a division National Institutes of Health «[ ] the UMLS project is an effort to overcome two significant barriers to effective retrieval of machine-readable information. The first is the variety of ways the same concepts are expressed in different machine-readable sources and by different people. The second is the distribution of useful information among many disparate databases and systems.» National Library of Medicine webpage

10 Purposes To enhance access to literature by facilitating the development of computer systems that understand biomedical language To design information retrieval or patient record systems To facilitate the communication between different systems To develop systems that parse the biomedical literature

11 Access Remote access UMLS Terminology Services (UTS) Browsers, Navigators APIs Download files and programs Documentation Local access MetamorphoSys: install files locally, create customized Metathesaurus subsets Subset Browser: search, browse, view customized subsets

12 Licence agreement Online Web-based license: Read license Read appendix Print a copy for your records Complete the Web form Verify: receive an from NLM; go to Web site within 72 hours and enter first and last name NLM official will countersign (turn-around time of a few days) Receive 2 nd from NLM with new license number

13 Knowledge sources Metathesaurus Semantic Network SPECIALIST Lexicon

14 Knowledge sources (2) Metathesaurus The base of UMLS 1 milion of biomedical concepts 5 milions of concept names organized by concept each concept has specific attributes defining its meaning is linked to the corresponding concept names in the various source vocabularies Semantic Network SPECIALIST Lexicon

15 Knowledge sources (3) Metathesaurus Semantic Network Each concept in the Metathesaurus is assigned one or more semantic types (categories), which are linked with one another through semantic relationships Semantic Network is a catalog of these semantic types and relationships The information about a semantic type includes an identifier, definition, examples, hierarchical information about the encompassing semantic type(s), and associative relationships. SPECIALIST Lexicon

16 Knowledge sources (4) Metathesaurus Semantic Network SPECIALIST Lexicon contains information about common English vocabulary, biomedical terms, terms found in MEDLINE terms found in the UMLS Metathesaurus

17 Metathesaurus The Metathesaurus: Very large Multi-purpose Multi-lingual The Metathesaurus contains information about: biomedical and health related concepts their various names and associated codes the relationships among them

18 Metathesaurus (2) Metathesaurus clusters terms by meaning: Concepts contain synonymous terms Preferred term is chosen (default can be changed) Concept Unique identifier (CUI) is assigned Wide range of general and specialized biomedical terminologies Used in variety of settings and purposes: Clinical Administrative Public Health Reporting Research

19 Metathesaurus, organization (3) Organization: organized by concept each concept has specific attributes defining its meaning each concept is linked to the corresponding concept names in the various source vocabularies numerous relationships between the concepts are represented: Hierarchical relationships is_a* is_part_of Associative relationships is_caused_by in_the_literature_often_occurs_close_to * is_a = is a kind of

20 Metathesaurus, uses (4) Uses of Metathesaurus: Information retrieval Thesaurus construction Natural language processing Automated indexing Electronic patient records Distribution of health data standard vocabularies

21 Metathesaurus, example (5) Example: Addison's Disease in medical vocabularies: Synonyms: different terms Addisonian syndrome {eponym} Bronzed disease {symptom} Addison melanoderma {symptom} Asthenia pigmentosa {symptom} Primary adrenal deficiency {clinical variant} Primary adrenal insufficiency {clinical variant} Primary adrenocortical insufficiency {clinical variant} Chronic adrenocortical insufficiency {clinical variant} Contexts: different hierarchies

22 Metathesaurus, example (6) Concept Unique Identifier (CUI)

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24 Metathesaurus, example (8)

25 Metathesaurus, example (9) Addison s disease Term source termtype source ID Addison s disease Metathesaurus PN Addison s disease SNOMED CT PT Addison s Disease MedlinePlus PT T1233 Addison Disease MeSH PT D Bronzed disease SNOMED Intl SY DB Primary Adrenal Insufficiency MeSH EN D Primary hypoadrenalism MedDRA LT syndrome, Addison

26 Metathesaurus, sources (10) What vocabularies are available in the UMLS Metathesaurus? There are more than 100 source vocabularies in the UMLS Metathesaurus, some in multiple languages. These include many different types of vocabularies and classifications, including clinical vocabularies, classifications, administrative code sets, and thesauri used to index and retrieve scientific literature. What is involved in adding a vocabulary to the UMLS Metathesaurus? There are four major steps in adding a vocabulary to the Metathesaurus: Analysis and Inversion Insertion Human Editing Quality Assurance

27 Semantic Network Each concept in the Metathesaurus is assigned one or more semantic types (categories), which are linked with one another through semantic relationships. The semantic network is a catalog of these semantic types and relationships. This is a rather broad classification: 135 semantic types 54 relationships in total

28 Semantic Network, types (2) The major semantic types: organisms anatomical structures biologic function chemicals events physical objects concepts or ideas The links among semantic types define the structure of the network and show important relationships between the groupings and concepts

29 Semantic Network, categories (3) The primary link between semantic types is the is_a link, establishing a hierarchy of types. The network also has 5 major categories of non-hierarchical (or associative) relationships, which constitute the remaining 53 relationship types: physically_related_to spatially_related_to temporally_related_to functionally_related_to conceptually_related_to

30 Semantic Network (4) #135 Semantic Types Broad subject categories (Clinical Drug, Virus) Example: Addison s Disease Semantic Type: Disease or Syndrome #54 Semantic Relationships Links between categories (is_a, causes, treats) Example: Virus causes Disease or Syndrome Types + Relationships Form the structure of the semantic network Broadly categorize the biomedical domain

31 Semantic Network (5) #54 Semantic Relationships: Hierarchical among types Animal is_a Organism Enzyme is_a Biologically Active Substance among relationships prevents is_a affects Non-hierarchical Sign or Symptom diagnoses Pathologic Function Pharmacologic Substance treats Pathologic Function

32 Semantic Network, usefulness (6) Why is it useful to have a Semantic Network? Semantic Types High level categories assigned to Metathesaurus concepts Independent of position in source hierarchies Semantic Relations Useful links between Semantic Types Relationships may hold at the concept level Other relationships may apply at the concept level

33 SPECIALIST Lexicon The SPECIALIST Lexicon contains information about: common English vocabulary biomedical terms terms found in MEDLINE terms found in the UMLS Metathesaurus. Each entry contains: morphological information (form and structure) syntactic information (how words are put together to create meaning) orthographic information (spelling)

34 SPECIALIST Lexicon, morpholgy (2) Morphology Inflection noun: nucleus, nuclei verb: cauterize, cauterizes, cauterized, cauterizingred adjective: red, reddest, redder Derivation verb noun adjectve noun cauterize cauterization red - redness

35 SPECIALIST Lexicon, ortography (3) Ortography Spelling variants oe/e oesophagus - esophagus ae/e anaemia - anemia ise/ize cauterise - cauterize genitive mark Addison's disease Addison disease Addisons disease

36 SPECIALIST Lexicon, syntax (4) Syntax Complementation: Verbs Nouns Intransitive I'll treat Transitive He treated the patient Ditransitive He treated the patient with a drug prepositional phrase Valve of coronary sinus

37 SPECIALIST Lexicon (5) Used by SPECIALIST Natural Language Processing System to process text and terms Customizable Used to maintain Metathesaurus, indexes

38 Lexical Tools Lexical tools JAVA programs to manage lexical variation, indexing, normalization in biomedical text Wordind breaks strings into words produces the Metathesaurus word indexes (MRXW) Lexical Variant Generation (Lvg) performs various lexical transformations 58 flow components and 38 options in 2006 NORM a selection of LVG transformations produces Metathesaurus normalized word and string indexes (MRXNW & MRXNS) used to access those indexes

39 Lexical Tools, Wordind (2) Wordind Wordind creates word indexes by breaking a string into a unique list of lowercased "words." Wordind defines a word as a sequence of one or more alphanumeric characters. For example, the phrase Increased heart rate in an overweight forty-year-old male would generate: increased heart rate overweight forty year old male WordInd reads from standard input and writes to standard output, one line per word. This tool is used by the UMLS to produce the word index for the Metathesaurus (the file named MRXW.RRF)

40 Lexical Tools, Lvg (3) Lvg - Lexical Variant Generation An important use of this library is to generate normalized terms for word indices. for example, the input terms swim, swam, and swum all normalize to the term swim Performs atomic lexical transformations generating inflectional variants

41 Lexical Tools, NORM (4) NORM The lexical program, Norm, generates the normalized strings for terms included in the SPECIALIST Lexicon. The normalization process involves stripping possessives replacing punctuation with spaces removing stop words such as "No Other Specification" or NOS lower-casing each word breaking a string into its constituent words sorting the words in alphabetic order.

42 Lexical Tools, NORM (5) NORM An example: Remove genitive Remove stop words Lowercase Strip punctuation Uninflect Sort words Hodgkin s diseases, NOS Hodgkin diseases, NOS Hodgkin diseases, hodgkin diseases, hodgkin diseases hodgkin disease disease hodgkin

43 Terminology Services (UTS) The UTS provides online access to the Knowledge Sources and other UMLS related resources. The UTS allows single sign-on access to all UMLS resources: terminology browsers, file downloads, reporting tools, and user profile management. The UTS includes updated versions of the Metathesaurus and Semantic Network browsers from the retired UMLSKS. Tree browsers are incorporated into the updated browsers. The UTS also incorporates a new browser: the SNOMED CT Browser.

44 Terminology Services (UTS) (2) The UMLS Terminology Services (UTS) is a computer application that provides Internet access to the UMLS Knowledge Sources. The purpose of the UTS is to make the UMLS data more accessible to users and, in particular, to systems developers. The system architecture is based on the client server model, allowing remote site users (individuals as well as computer programs) to send requests to a centrally managed server at the U.S. National Library of Medicine.

45 Terminology Services (UTS) (3) Access to the system is provided through a command line interface, through the World Wide Web, an Extensible Markup Language (XML)-based socket programming interface, and through an Application Programmer Interface (API).

46 Querying the UMLS Terminology Services (UTS) Metathesaurus browser Semantic Network browser SNOWMED CT browser We will use it during next UMLS practise lesson

47 Querying the UMLS Terminology Services (UTS) (2) Metathesaurus browser: search of Addison's disease

48 Querying the UMLS Terminology Services (UTS) (3) Metathesaurus browser: search of Addison's disease

49 Querying the UMLS Terminology Services (UTS) (4) Metathesaurus browser: search of Addison's disease

50 Querying the UMLS Terminology Services (UTS) (5) Semantic Network browser: search of Physical object

51 Querying the UMLS Terminology Services (UTS) (6) Snowmed CT browser: search of term

52 Further readings Further readings Official UMLS website UMLS overview and tutorial by Rachel Kleinsorge, Jan Willis, Allen Browne, Alan Aronson (NIH, Usa) Revising the UMLS Semantic Network by Steffen Schulze-Kremer, Barry Smith, Anand Kumar (University of Leipzig, Germany)

53 Terminology Service registration UMLS registration For tomorrow practice lesson, you need to register TODAY on UMLS Terminology Service website Official UMLS Terminology Service website