Contenu connexe Similaire à Elsevier Smart Content LDR SemTech NYC Oct-17-2012 (20) Elsevier Smart Content LDR SemTech NYC Oct-17-20121. Elsevier Health Sciences
Smart Content Drives Smart Applications
The Future Of Using Knowledge In Healthcare
SemTechBiz 2012 Conference Alan Yagoda
October 17, 2012 VP, Business Technology
a.yagoda@elsevier.com
@alanyagoda
2. About Elsevier
Elsevier is the largest Science, Technical and Medical
Publisher in the world. In the area of Health Sciences,
Elsevier publishes leading brands including The Lancet,
Braunwald’s Heart Disease, Gray’s Anatomy, and the Netter
Atlases among others. In addition, Elsevier produces leading
online clinical support tools and products including:
• Clinical Key
• MD Consult
• Procedures Consult
• Mosby’s Nursing Consult
• CPMRC Nursing Care Plans
• Gold Standard Drug Database
• MEDai Analytics for Managed Care Plans
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4. The Challenge: Getting doctors the right information to make
the best decisions and provide the best clinical care
Trusted:
Authoritative medical and surgical content from Elsevier.
Comprehensive:
Integrated Medline and 3rd party content.
Speed To Answer:
Fast discoverability of the most relevant answers and
more intuitive searching.
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5. Introducing
Smart Content
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6. Taxonomy-Powered Content = Smart Content
Content
with
applied
taxonomy
Content
today
with
structured
XML
Copyright 2011 Outsell Gilbane Services, Inc.
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http://www.outsellinc.com
http://gilbane.com/xml/2009/11/what-is-smart-content.html#ixzz0hnuRhaBc
7. Smart Content At Elsevier
Smart Content Applications
Better discovery through
semantic search & navigation
Linked data from
• Faceted search & browse
partners and the Web
• Ontology-driven navigation
• Task-specific results
• Personalized/localized results
• Link to evidenced-based content"
Text Better understanding through
Elsevier Entities, analysis and visualization
Content concepts • Question & Answer"
• Actionable Content & Alerts"
Partner Tables and • Tag clouds
• Heatmaps"
Content relationships • Animations"
Images
New knowledge through
aggregation and synthesis
• Topic pages
Elsevier • Social network maps
knowledge • Geolocation maps
organization
• Data integration and mashups"
systems • Text mining "
• Inference and Reasoning
7
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8. Making Smart Content Work in the Clinical Setting
Clinical
Clinical
Trials
Journals
Summaries
Guidelines
Procedural
Drug
Info
PaIent
Ed
Books
Videos
Elsevier Merged Medical Taxonomy (EMMeT)
250K+
Core
Clinical
Concepts
EMMeT
Concept
Mapping
Elsevier
1M+
Synonyms
Custom
1M+
Hierarchical
RelaIonships
1M+
Ontological
RelaIonships
UMLS
•
Vast
amounts
of
content
made
easily
discoverable
•
Specialty-‐specific
naviga9on
•
Dynamic
clinical
summary
crea9on
•
Meaningful
related
content
recommenda9ons
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9. Introducing EMMeT (Elsevier Merged Medical Taxonomy)
Parent Terms
• Breast Disorders 2
• Cancer of the Thorax
• Mammary Neoplasms
• More….
Symptoms Breast Lump, Nipple Retraction, …..
Medical Name
Diagnostic
Malignant Neoplasm of the Breast Mammography, Breast Biopsy, …..
Procedures
Consumer Friendly Name
Breast Cancer
Synonyms 1 4
Malignant Tumor of Breast Treatment
Chemotherapy, Mastectomy, ….
Malignant Breast Neoplasm Procedures
Semantic Relationships
Breast Ca
Codes
ICD9 – 174.9
MeSH – D001943 Medications Tamoxifen, Doxorubicin, …..
SNOMED-CT – 190121004
Semantic Type/Group
Neoplastic Process/Disease
Risk Factors Family History, Genetics, Predisposition, ….
Children Terms
• Breast Sarcoma
3 Prevention Screening, Preemptive Mastectomy, ….
• Familial Breast Cancer
• Malignant lymphoma of the Breast
• Malignant Neoplasm of the breast outer
quadrant Complications Metastatic Cancer, ….
• More…
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10. Automated Indexing: Weighted Tags for Better Search
Article-level SMART Content tags help
confirm relevance and provide a topical
overview about a piece of content.
Paragraph-level SMART Content tags
uncover highly-relevant information not
necessarily evident from the title or
abstract alone.
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13. Linked Data Repository (LDR): Warehouse for
Smart Content Enhancements
Delirium treatment: An unmet challenge
Title • Service platform that provides a rich
Rivastigmine, a cholinesterase inhibitor, has been used to semantic layer that enables search and
treat delirium in elderly patients with stroke. 1 A biologically
plausible premise—that impaired cholinergic transmission discovery of metadata.
Disease
might either cause or worsen delirium—led to a
randomised, placebo-controlled, double-blind trial by
Drug
Maarten van Eijk and colleagues 2 in The finding which
Clinical Lancet in • Transforms content into knowledge data
they added rivastigmine or placebo to usual treatment of
patients in intensive care. The trial was halted at 104 to allow exploration of extracted
patients by the drug safety and monitoring board (DSMB)
because of increased mortality (12/54 in the rivastigmine
knowledge, content analysis, and
group, 4/50 in the placebo group; p=0·07) and a worse visualization.
outcome. The rivastigmine group …
• Enhances extracted knowledge of
Elsevier assets by interlinking data with
related sources of medical and scientific
Elsevier owl:same as
content and data.
med:diseases
Delirium
ATC:
N06DA03
med:drugs
RivasIgmine
Drug:
RivasIgmine
• Optimized for high-volume read-write for
owl: same as use by end-user products.
foaf:page
LinkedCT
• Provide service layer APIs for ease of
Trial:
NCT00623103
Serious
Adverse
events:
Trial:
NCT00623103
integration.
Atrial
fibrillaIon
IntervenIon:
RivasIgmine
CondiIon:
Delirium
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14. Represent Enhancements and Vocabularies In RDF
Satellites
Creation of Satellite Standards
• Linked data compliant RDF representing metadata objects
• Leverage common namespaces from dct, pav, rdf, skos
• Taxonomies in SKOS to enhance portability in the linked data world
• Subject tagging against a vocabulary representing extracted
knowledge LDR
• Concept URIs that can be equated to URIs in linked data
• Support RDF/XML and Turtle
Example RDF Statements
Tags from a taxonomy for a given document
Document sections relevant to a given concept
Document sections providing answers to a given question
Genes mentioned in a given document
Documents supporting or disputing conclusions of a given document
Concepts in the areas of expertise for a given author
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15. LDR Semantic Infrastructure
Linked Data & Linked Data Loader
3rd Party Data
Data
Space
Services
Vocab &
Annotation
AnnotaIon
Linked
Data
Satellites
Satellites
Satellites
3rd
Party
RDF
Vocab
Asset
Data
Satellites
Smart Content Indexing Pipeline
Linked
Data
Pipeline
Services
(Hadoop)
AWS Cloud Management
EMMeT Vocabulary
SKOS
Semantic
Ontology Svcs
GeneraIon
RDF Loader
Interlinking
Reasoning
Transform
Analytics
Network
N-Quads
Extract
JSON
…
Tagging
and
Indexing
Content
Elsevier
Services
(Concepts,
Chapters,
ArIcles,
Guidelines,etc)
RDF
GeneraIon
Discovery Services (Semantic Knowledgebase)
3rd
Party
Content
Content
InsIt.
Amazon MongoDB SOLR/ Virtuoso
S3 NoSQL SIREn Triplestore
Product-specific
Smart Content Access & Admin &
Atom Feed Analytics
Search Index Entitlements Monitoring
Discovery Svc Ontology
SPARQL Alerts
API (REST) Service
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16. Smart Content In Action
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18. Trend Analysis Of Special Health Topics (Mashups)
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20. Comprehensive Drug Reference
• Moving world-class content online to Point of Care.
• Extracted knowledge is linked for further enrichment.
• Information is condensed, immediate and actionable.
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22. Linking Patient Data To Evidence-Based Research
• Recommended
research
relevant
to
a
paIent
profile
• InfoBu^on
integraIon
• Alerts
on
FDA
Announcements.
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24. What We Learned On Our Journey To Adoption
• Focus
on
business
value
-‐
POCS
are
invaluable.
Organiza2onal
• Requires
different
skillsets.
Readiness
• Break
from
tradiIonal
IT
and
follow
consumer
Internet
businesses.
• Cloud
to
combine
big
data
and
semanIcs
at
scale.
• Product
and
data
integraIon
just
got
easier.
Technical
• Need
access
points
besides
SPARQL.
• Won’t
get
it
right
the
first
Ime
-‐
Fail
fast
and
cheap.
• Pick
standards
that
are
pracIcal
and
ease
adopIon.
Data
• Be
paranoid
about
freshness
and
quality
of
linked
data.
• OpImize
for
performance
–
more
triples
isn’t
always
be^er.
24
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25. Thank you.
Alan Yagoda
a.yagoda@elsevier.com
@alanyagoda
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