10,000 foot view of what i am working on
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10,000 foot view of what I am working on. Wendy W. Chapman, PhD. Biomedical Language Understanding. University of Pittsburgh. Dept of Biomedical Informatics. Background. U of Utah. Wisconsin. U of Utah. U of Pittsburgh. 1992. 1994. 2000. 2003. BA Linguistics. Post-doc BMI. - PowerPoint PPT PresentationTRANSCRIPT
10,000 foot view of what I am working on
Wendy W. Chapman, PhD
University of Pittsburgh
Dept of Biomedical Informatics
Biomedical Language Understanding
BackgroundB
A L
ingu
istic
sB
A L
ingu
istic
s
Chi
nese
Lite
ratu
reC
hine
se L
itera
ture
1992 1994
PhD
Med
ical
Info
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ics
PhD
Med
ical
Info
rmat
ics
Pos
t-do
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MI
Pos
t-do
c B
MI
Fac
ulty
DB
MI
Fac
ulty
DB
MI
20032000
U of UtahU of Utah WisconsinWisconsin U of UtahU of Utah U of PittsburghU of Pittsburgh
Biomedical Language Understanding
www.dbmi.pitt.edu/blulabHenk Harkema, Danielle Mowery, Mike Conway,Lee Christensen, Qi Li, Wendy Chapman
Temporality Schema
Topaz
NLP Repository
AnaphoricReference
Onyx
BLU Lab NLP Sampler
OntologyEnrichment
ResultsReview/Error
Analysis
OntologyFor
SyndromicSurveillance
Temporality Schema
Topaz
NLP Repository
AnaphoricReference
Onyx
BLU Lab NLP Sampler
OntologyEnrichment
ResultsReview/Error
Analysis
OntologyFor
SyndromicSurveillance
Topaz
• Named entity recognition– Maps UMLS concepts to higher-level concepts
• Contextual property assignment (ConText)– Existence (affirmed, negated)– Experiencer (patient, other)– Historicity (current, historical)– Realis (actual, non-specific/hypothetical)– Certainty (uncertain, certain)– Reason for exam (yes, no)– Quality of exam (diagnostic, limited)
Harkema, B Chapman, Hwa
ConText: Determine Values for Contextual Properties
Patient denies cough but complains of headache.No change in the patient’s chest pain.
trigger term
terminationtermpseudo-trigger
term
scope
Clinical condition: CoughNegation: Negated
ConText: Historical
Past history of pneumonia presentingtoday with cough and fever.
trigger term terminationterm
scope
Clinical condition: PneumoniaTemporality: Historical
Temporality Schema
Topaz
NLP Repository
AnaphoricReference
Onyx
BLU Lab NLP Sampler
OntologyEnrichment
ResultsReview/Error
Analysis
OntologyFor
SyndromicSurveillance
Onyx
Onyx
At (translucency, numberEight) &
surfaceOf (numberEight, mesial) &
stateOf (translucency, possible)
Semantic Models
Semantic Models
Syntactic AnalyzerSyntactic Analyzer
Context-free Grammar
Context-free Grammar
TrainingCorpusTrainingCorpus
Semantic AnalyzerSemantic Analyzer
Eight mesial might have a slight translucency
Haug, Schleyer
Knowledge-rich Frame-based Mapping
ProbabilisticFrames
SemanticNetwork
- Frame slots map to semantic network- Relationships between slots are probabilistic
Annotation Interfacewith active learning and help from Onyx
TemplatesTemplates
Semantic ModelSemantic Model
Speech NLP Chart
Onyx
Dental ExamsNumber one Is missing. Two is fine. Caries on Tooth 3.
Titus Schleyer, Lee Christensen, Peter Haug, Jeannie Irwin, Henk Harkema
Temporality Schema
Topaz
NLP Repository
AnaphoricReference
Onyx
BLU Lab NLP Sampler
OntologyEnrichment
ResultsReview/Error
Analysis
OntologyFor
SyndromicSurveillance
Ontology Development-Information Extraction (ODIE)
Ontology
Text
Ontology EnrichmentUse IE to find new concepts and relationships to add
Information ExtractionUse ontology to improve IE from text
Rebecca Crowley, Mayo Clinic, Stanford NCBO
SurgicalPathologySurgical
PathologyChest
RadiographyChest
Radiography
View Overlap of Ontologies
Suggest Concepts
Temporality Schema
Topaz
NLP Repository
AnaphoricReference
Onyx
BLU Lab NLP Sampler
OntologyEnrichment
ResultsReview/Error
Analysis
OntologyFor
SyndromicSurveillance
Results Review/Error Analysis
Temporality Schema
Topaz
NLP Repository
AnaphoricReference
Onyx
BLU Lab NLP Sampler
OntologyEnrichment
ResultsReview/Error
Analysis
OntologyFor
SyndromicSurveillance
Schema for Clinical Condition Properties
Properties of Condition Concept
Existence Yes, NoExperiencer Patient, OtherChange Unmarked, Unchanging, Changing, Increasing, Decreasing,
Improving, Worsening, RecurrenceIntermittent Unmarked, Yes, NoCertainty Unmarked, High, Moderate, LowMental State Yes, NoGeneralized/Conditional Yes, NoCurrent Visit Relation Before, Meets_Overlaps, After
Wiebe, Jordan, Mowery, Harkema
Schema for Temporal Relations
Time Words Points, DurationsOrdering Words Precedes, During, FollowsAspectual Words Initiation, Continuation, Culmination
Temporality Schema
Topaz
NLP Repository
AnaphoricReference
Onyx
BLU Lab NLP Sampler
OntologyEnrichment
ResultsReview/Error
Analysis
OntologyFor
SyndromicSurveillance
Temporality Schema
Topaz
NLP Repository
AnaphoricReference
Onyx
BLU Lab NLP Sampler
OntologyEnrichment
ResultsReview/Error
Analysis
OntologyFor
SyndromicSurveillance
Application Ontology for Syndromic Surveillance
Consensus of developers/users across countryConway, Buckeridge
Temporality Schema
Topaz
NLP Repository
AnaphoricReference
Onyx
BLU Lab NLP Sampler
OntologyEnrichment
ResultsReview/Error
Analysis
OntologyFor
SyndromicSurveillance
Anaphoric Reference in Clinical ReportsCrowey, Savova, Zeng
• Adapted MUC schema for clinical reports• Three experts annotated 180 reports
Five types—Mayo, UPMC
• identity• part/whole• set/subset
• Characterize anaphoric reference in reports• Train/test resolution algorithms