the neighborhood auditing tool james geller yehoshua perl c. paul morrey

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The Neighborhood Auditing Tool James Geller Yehoshua Perl C. Paul Morrey

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Page 1: The Neighborhood Auditing Tool James Geller Yehoshua Perl C. Paul Morrey

The Neighborhood Auditing Tool

James GellerYehoshua PerlC. Paul Morrey

Page 2: The Neighborhood Auditing Tool James Geller Yehoshua Perl C. Paul Morrey

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Participating Student Developers

Dayanand Sagar Kushal Chopra Sandeep Ramachandran Anisa Vishnani Aditi Dekhane Kandarp Shah Rajesh Gupta Suraj Pal Singh Saurabh Patel

Kartik Gopal Yakup Kav Rahul Bhave Sirish Motati Pratik Shah Saurabh Singhi Sirish Motati Reddy Sandeep Pasuparthy Ramya Gokanakonda

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Overview

Goals of an Auditor’s Tool for the UMLS Principles of Auditing with Neighborhoods The Idea of a Hybrid Display Current State of the NAT: Serving the Auditor Feature Presentation Live Audit Session Planned State of the NAT: Guiding the Auditor Conclusions and Future Work

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Auditing the UMLS

The UMLS consists of over 100 terminologies.

It is natural that inconsistencies will appear Over 1.5 million concepts and over 7

million terms Two level structure consisting of the

Semantic Network and the Metathesaurus

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How We did it before the NAT: Paper Form

CPT: C1081844 Antonospora locustaeSRC: NCBISTY: T004T009 Fungus + InvertebrateDEF:SYN: Antonospora locustae | Nosema locustaePAR: Antonospora{STY: Invertebrate}CHD:

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Previous Work on Auditing H. Gu, Y. Perl, J. Geller, M. Halper, L. Liu, and J.J. Cimino.

Representing the UMLS as an Object-oriented Database: Modeling Issues and Advantages. J Am Med Inform Assoc, 7(1):66-80, 2000.

J. Geller, H. Gu, Y. Perl, and M. Halper. Semantic refinement and error correction in large terminological knowledge bases. Data & Knowledge Engineering, 45(1):1-32, 2003.

Y. Chen, Y. Perl, J. Geller, and J.J. Cimino. Analysis of a study of the users, uses, and future agenda of the UMLS. J Am Med Inform Assoc, 14(2):221-231, 2007.

H. Gu, G. Hripcsak, Y. Chen, C.P. Morrey, G. Elhanan, J.J. Cimino, J. Geller, and Y. Perl. Evaluation of a UMLS auditing process of semantic type assignments. In J.M. Teich, J. Suermondt, and G. Hripcsak, editors, Proc AMIA Symp, pages 294-298, Chicago IL, Nov. 2007.

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Auditing Results Paper Form(C1081844) Antonospora locustaeSTY: Fungus + Invertebrate

No errors Semantic Type Error: Fungus Semantic Type Error: Invertebrate Ambiguity Add Semantic Type______________________ Other error_____________________________ Comments _____________________________

______________________________________

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Goals of an Auditor’s Tool for the UMLS

Display relevant information to the auditor. Do not overwhelm the auditor with too

much information. Helps the auditor focus on areas most

likely to contain errors.Neighborhood display of reviewed conceptsAlgorithms suggest likely erroneous concepts

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Principles of Auditing with Neighborhoods

Several years of experience: Auditing is to a large degree a “local” activity.

Concepts have two kinds of knowledge elements:Textual Knowledge Elements: Preferred term,

CUI, synonyms, LUI, definition, sources, semantic types

CONtextual Knowledge Elements: Neighbors

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Neighborhoods

Focus concept: The concept presently under review

Immediate Neighborhood: The set of concepts reachable from the focus concept by stepping one relationship (up, down, lateral, etc.)

Extended neighborhood: Includes parents of parents (grandparents), children of children (grandchildren) and siblings. No lateral chains.

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Immediate Neighborhood

Microsporidia, Unclassified

Microsporidia <protozoa>

Dictyocoela Edhazardia

FibrillanosemaMicrosporidium

Kabatana

Oligosporidium

Cellular aspects of

Microbiological

Pathogenicity Aspects

virologic

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Extended Neighborhood

RELATIONSHIPS

SIBLINGS

GRANDCHILDREN

CHILDREN

FOCUS CONCEPT

PARENTS

GRANDPARENTS

Microsporidia, Unclassified

Microsporidia <protozoa>

Erroneous concept

fungus

PHYLUM MICROSPORA

Protozoa

Sporozeoa

Dictyocoela Edhazardia

FibrillanosemaMicrosporidium

Dictyocoela berillonum

Dictyocoela cavimanum

Edhazardia aedis

Fibrillanosema crangonycis

Microsporidium 57864

Dictyocoela dehayesum

Dictyocoela duebenum

Dictyocoela grammarellum

Dictyocoela muelleri

Dictyocoela sp.L11

Kabatana

Kabatana takedai

Microsporidium africanum

Microsporidium ceylonensis

Microsporidium cypselurus

Microsporidium prosopium

Microsporidium seriolae

Oligosporidium

Oligosporidium occidentalis

Microsporea

Cellular aspects of

Microbiological

Pathogenicity Aspects

virologic

SIB

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Up-Extended and Down-Extended Neighborhood

An up-extended neighborhood includes grandparents and the immediate neighborhood.

A down-extended neighborhood includes grandchildren and the immediate neighborhood.

Give auditor all s/he needs but not more.

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Semantic Type Neighborhood

If we provide the semantic types for every concept, those also form a neighborhood.

It is important to keep the information which semantic types belong to which concepts.

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References about Neighborhood M.S. Tuttle, D.D. Sherertz, N.E. Olson, M.S. Erlbaum, W.D.

Sperzel, and L.F. Fuller, et al. Using META-1, the first version of the UMLS Metathesaurus. In Proc 14th Annu Symp Comput Appl Med Care, pages 131-135, Washington, D.C., 1990.

S.J. Nelson, M.S. Tuttle, W.G. Cole, D.D. Sherertz, W. D. Sperzel, M.S. Erlbaum, L.L. Fuller, N.E. Olson, From meaning to term: semantic locality in the UMLS Metathesaurus. In Proc Annu Symp Comput Appl Med Care, pages 209-213, Washington, D.C., 1991.

J.J. Cimino, H. Min, and Y. Perl. Consistency across the hierarchies of the UMLS Semantic Network and Metathesaurus. J Biomed Inform, 36(6):450-461, 2003.

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Desirable Information Beyond Neighborhoods

Concept definition for Focus Concept Concept sources for Focus Concept Assigned Semantic Types of concepts Definitions of relevant Semantic Types Global view of the Semantic Network

Indented (better for wide branches)Graphical (better for almost everything else)–

we set the standard on this.

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The Idea of a Hybrid Display

Diagrams are wonderful – as long as they fit on one screen.

Indented text is wonderful – as long as there are no or very few multiple parents.

But the UMLS does not fit onto one screen and there are many cases of multiple parents.

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WHAT makes a diagram wonderful?

You can follow parent/child paths with your eyes.

You can get a feeling for everything a concept is connected to with one look.

You can see multiple parents and paths with one look.

You can see global features (short and bushy versus tall and sparse, or (gasp) tall and bushy).

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What makes Indented Text Wonderful?

Indentation expresses parenthood elegantly.

There are no lines crossing. You don’t need a layout algorithm. There is a linear order in which to study

text.

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The Idea of a Hybrid Display (cont.)

Keep the best features of text and the best features of diagrams.

Maintain relative positions between the focus concept and its children, parents, etc.

Eliminate clutter of arrows.

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A Hybrid Diagram/Form Display of a Neighborhood

Children

Focus ConceptSynonyms Relationships

Parents

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Important Auditing Principles

If a concept C has a combination of semantic types assigned, and very few other concepts C1…Cn (n < 6) have that same combination assigned, then C and C1…Cn are suspicious concepts.

We call this “a small intersection.” Group-based auditing: Audit sets of similar

concepts. Y. Chen, H. Gu, Y. Perl, J. Geller, and M. Halper. Structural group

auditing of a UMLS semantic type’s extent. J Biomed Inform, 2007. Accepted for publication.

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Current State of the NAT: Serving the Auditor

The Neighborhood Auditing Tool has been implemented to fully support display of neighborhoods.

Navigation to “adjacent neighborhoods” is easy.

Additional features listed before have been implemented.

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Demonstration of NAT Features

Neighborhood Relationships Siblings Grandparents and

grandchildren Synonyms Focus concept definition Focus concept sources Semantic Type display Semantic Type definition

Semantic Network (indented)

Semantic Network (diagram)

Display Options Navigation Search Viewing History UMLS version

offline version

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Audit Example

An algorithm determined that the concept Antonospora locustae was likely assigned incorrect semantic types.

We follow an auditor’s review of this concept using the data from 2007AA.

offline version

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Preliminary Evaluation Study with NAT

Compare paper-based auditing and NAT-based auditing.

Counterbalanced groups. Recall improves with NAT use. Auditors

seem willing to investigate more concepts. Precision stays the same. Auditors’ mental

process does not improve (?).

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Planned State of the NAT:Guiding the Auditor by Finding

(i.e. Computing) Audit Sets As noted before, errors are likely in small

intersections. Planned new version of the NAT will compute

and display small intersections. Errors are clearly visible in small groups of

supposedly similar concepts. Planned new version of the NAT will compute

small groups of supposedly similar concepts.

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Finding Successively Smaller Groups of Concepts

Finding Audit sets by selecting:

1. Concepts with same semantic type.

2. Concepts with 1. and same root.

3. Concepts with 1. and 2. that have the same relationships.

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A

B

C D

E

LEGEND

concept

PAR/CHD relationship

area

EXTENT OF A SEMANTIC TYPE

Area A

Area B

Area C Area D

Area E

Other relationship

r1 r3

r'3

r2

r4

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Audit Set Examples Example A A selection of concepts in

the intersection of Manufactured Object + Organization under the root School (environment).

Example B All concepts that are in a non-chemical intersection with an extent size less than five.

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Possible Auditor’s Recommendations (see Pg. 7)

Mark concept as reviewed and correct. Mark semantic types that should be

removed. Mark semantic types that should be

added. Mark other kinds of errors. Attach notes to a reviewed concept.

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Conclusions and Future Work

Preliminary study showed that people are more successful finding errors with NAT than with paper sources.

Recall improved with the NAT, precision did not.

NAT seems to nicely complement use of the UMLSKS.

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Conclusions and Future Work (cont.)

This year, work with more human subjects to quantify these observations.

Integration of algorithms for finding audit sets with NAT.By extent sizeUsing roots, and relationship patterns

within extents.

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Auditor

Errors Recall Precision F

with NAT

w/o NAT

with NAT

w/o NAT

with NAT

w/o NAT

with NAT

w/o NAT

1 57 45 0.97 0.82 0.53 0.51 0.86 0.63

2 22 20 0.43 0.35 0.55 0.55 0.48 0.43

3 39 34 0.64 0.58 0.46 0.53 0.54 0.55

4 56 44 0.55 0.54 0.30 0.34 0.39 0.42

Avg. 44 36 0.65 0.57 0.46 0.48 0.57 0.51

Preliminary Evaluation Study

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Improved Recall

The auditor finds it easy to search for more errors in the neighborhood of the suspicious concept.

With better recall and the same precision you still find more errors.

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Auditing Demonstration

The concept Antonospora locustae was selected for audit by an algorithm that found it was the only concept assigned to the intersection Fungus + Invertebrate in the UMLS 2007AA.

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NAT Features Demonstration

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Neighborhood

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