= i2b2 AUG 2013 =

== Program ==
=== NLP Workshop ===

1. [#NLP1 UMLS Ontologies and Ontology Resources] ''(Olivier Bodenreider)''
1. [#NLP2 Ontology-based De-identification of Clinical Naratives] ''(Finch and !McMurry)''
1. [#NLP3 Ontology-based Discovery of Disease Activity from the Clinical Record] ''(Lin)''
1. [#NLP4 Ontology Normalisation of the Clinical Narrative] ''(Chen)''
1. [#NLP5 Ontology Concept Selection] ''(Yu)''
1. [#NLP6 Active Learning for Ontology-based Phenotyping] ''(Dligach)''
1. [#NLP7 Conclusion]

=== Academic User Group ===

1. [#AUG1 Genomic Cell] ''(Shawn Murphy and Lori Philips)''
1. [#AUG2 SMART Apps] ''(Wattanasin)''
1. [#AUG3 i2b2 Roadmap] ''(Shawn Murphy)''
1. [#AUG4 Planning for the future] ''(Kohane)''
1. [#AUG5 From Genetic Variants to i2b2 using NoSQL database] ''(Matteo Gabetta - Pavia)''
1. [#AUG6 Extending i2b2 with the R Statistical Platform]
1. [#AUG7 Integrated Data Repository Toolkit (IDRT) and ETL Tools] ''(Sebastian Mate - Erlangen; Christian Bauer - Goettingen)''

=== i2b2 SHRINE Conference ===

1. [#SHRINE1 SHRINE Clinical Trials (CT) Functionality and Roadmap] ''(Shawn Murphy)''
1. [#SHRINE2 SHRINE National Pilot Lessons Learned]
1. [#SHRINE3 SHRINE Ontology Panel]
1. [#SHRINE4 University of California Research Exchange (UC ReX)] ''(Doug Berman)''
1. [#SHRINE5 Preparation for Patient-Centred Research] ''(Ken Mandl)''
1. [#SHRINE6 Case Study: Improve Care Now] ''(Peter Margolis)''

== NLP Workshop ==

=== [=#NLP1 UMLS Ontologies and Ontology Resources] ===

Presentation showing how UMLS resources can be used with NLP to extract information from free text.

NLP has two stages:

1. Entity Recognition - Identifying important terms within text
1. Relationship Extraction - linking entities together

==== Entity Recognition ====

Three major problems when identifying entities within a text:

1. Entities are missed
1. Entities are partially matched - part of the term is matched but another part is missed leading to incomplete information or context.  For example, in the term 'bilateral vestibular' only the second word may be matched.
1. Ambiguous terms - terms that may have two meanings.

Entities are identified by a combination of normalisation and longest term matching.

Normalisation is the process whereby a term is manipulated to produce a form of words that will match a large number of potential matches.  The process involves removing noise words, standardising inflections and derivatives (e.g., remove plural), converting to lower case, and sorting the words into alphabetical order.

In order to extract the most meaning from the text, an attempt is made to try to match the term with the most number of matching words.  For example, 'left atrium' as opposed to just 'atrium'.

==== Types of Resources useful for Entity Recognition ====

There are several types of resource:

1. Lexical resources - lists of terms with variant spellings, derivatives and inflections, associated with the part of speach to which they refer.  These can be either general or include specialist medical terms.
1. Ontologies - set of entities with relationships between the entities.
1. Technical resources - set of terms and identifiers used to map a term to an ontology.
1. Hybrid - A mixture of 1 and 2.  They are not strictly speaking ontologies as the relationships may not always be true (e.g., a child may not always be a part of the parent).  They are useful for finding terms, but should not be used for aggregation.

==== Lexical Resources ====

1. [[http://lexsrv3.nlm.nih.gov/Specialist/Home/index.html|UMLS Specialist Lexicon]] - Medical and general English
1. [[http://wordnet.princeton.edu/|WordNet]] - General English
1. [[http://lexsrv2.nlm.nih.gov/LexSysGroup/Projects/lvg/2012/docs/userDoc/tools/lvg.html|LVG Lexical Variant Generation]] - specialist tool
1. [[http://www.ebi.ac.uk/Rebholz-srv/BioLexicon/biolexicon.html|BioLexicon]] - EU project.  Not as general.  Mainly focused on genes.
1. [[http://pir.georgetown.edu/pirwww/iprolink/biothesaurus.shtml|BioThesaurus]] - Focused on proteins and genes.
1. [[http://www.nlm.nih.gov/research/umls/rxnorm/|RxNorm]] - Drug specific.

==== Ontological Resources ====

1. [[http://semanticnetwork.nlm.nih.gov/|UMLS Semantic Network]]

==== Terminology Resources ====

1. [http://www.nlm.nih.gov/research/umls/knowledge_sources/metathesaurus/index.html|UMLS MetaThesaurus]
 * Groups terms from many ontologies
 * Produces a graph of all the relationships
 * Graph is not acyclic and contains contradictions ''because'' it reproduces its source ontologies exactly.
 * Allows standards to be mapped between. 
1. [[http://www.nlm.nih.gov/research/umls/rxnorm/|RxNorm]]
 * Map between many drug lists.
 * Map between branded and generic drug names.
1. [[http://metamap.nlm.nih.gov/|MetaMap]]
 * Free with licence agreement
 * Based on UMLS MetaThesaurus.
 * Parses text to find terms.
 * Used in IBM's Watson tool.
 * Terms can be translated between various standards, including Snomed.
 * Copes with term negation and disambiguation.
1. [[http://www.nactem.ac.uk/software/termine/|TerMine]]
1. [[http://www.ebi.ac.uk/webservices/whatizit/info.jsf|WhatIzIt]]

==== Relationship Extraction ====

1. [[http://skr.nlm.nih.gov/|SemRep]]

==== Orbit Project ====

The [[http://orbit.nlm.nih.gov|Orbit Project]] is the Online Registry of Biomedical Informatics Tools.


=== [=#NLP2 Ontology-based De-identification of Clinical Naratives] ===
=== [=#NLP3 Ontology-based Discovery of Disease Activity from the Clinical Record] ===
=== [=#NLP4 Ontology Normalisation of the Clinical Narrative] ===
=== [=#NLP5 Ontology Concept Selection] ===
=== [=#NLP6 Active Learning for Ontology-based Phenotyping] ===
=== [=#NLP7 Conclusion] ===

== Academic User Group ==

=== [=#AUG1 Genomic Cell] ===
=== [=#AUG2 SMART Apps] ===
=== [=#AUG3 i2b2 Roadmap] ===
=== [=#AUG4 Planning for the future] ===
=== [=#AUG5 From Genetic Variants to i2b2 using NoSQL database] ===
=== [=#AUG6 Extending i2b2 with the R Statistical Platform] ===
=== [=#AUG7 Integrated Data Repository Toolkit (IDRT) and ETL Tools] ===

== i2b2 SHRINE Conference ==

=== [=#SHRINE1 SHRINE Clinical Trials (CT) Functionality and Roadmap] ===
=== [=#SHRINE1 SHRINE National Pilot Lessons Learned] ===
=== [=#SHRINE1 SHRINE Ontology Panel] ===
=== [=#SHRINE1 University of California Research Exchange (UC ReX)] ===
=== [=#SHRINE1 Preparation for Patient-Centred Research] ===
=== [=#SHRINE1 Case Study: Improve Care Now] ===