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Medical data and text mining
Linking diseases, drugs, and
adverse reactions
Lars Juhl Jensen
structured data
Jensen et al., Nature Reviews Genetics, 2012
unstructured data
central registries
hospital EHR systems
opt-out
opt-in
registry data
civil registration system
established in 1968
CPR number
Jensen et al., Nature Reviews Genetics, 2012
national discharge registry
14 years
6.2 million patients
45 million admissions
68 million records
119 million diagnosis
ICD-10
Jensen et al., Nature Reviews Genetics, 2012
not research
reimbursement
diagnosis trajectories
comorbidity
contingency table
Jensen et al., Nature Reviews Genetics, 2012
confounding factors
“known knowns”
gender
age
type of hospital encounter
Jensen et al., Nature Communications, 2014
“known unknowns”
smoking
diet
“unknown unknowns”
reporting biases
matched controls
proxy diagnoses
temporal correlations
diagnosis trajectories
Jensen et al., Nature Communications, 2014
trajectory networks
Jensen et al., Nature Communications, 2014
key diagnoses
Jensen et al., Nature Communications, 2014
direct medical implications
clinical text
unstructured data
free text
Danish
complex terminology
busy doctors
abbreviations
misspellings
a lot of it
computer
as smart as a dog
teach it specific tricks
named entity recognition
comprehensive dictionary
diseases
drugs
adverse drug reactions
synonyms
orthographic variation
flexible matching
hyphens and spaces
expansion rules
spelling variants
Clozapine
Clozapine
clozapi
n
clossapi
n
klozapin
e
chlosapi
n
chlosapi
ne
chlozapi
n
chlozapi
ne
klossapi
n
closapin
e
klozapi
nklosapi
n
“black list”
pest eller kolera
pharmacovigilance
clinical trials
spontaneous reports
underreporting
text/data mining
medication
Jensen et al., Nature Reviews Genetics, 2012
adverse events
hand-crafted rules
Eriksson et al., Drug Safety, 2014
Drug introduction Drug discontinuationAdverse event
Adverse eventNegative modifier Indication Pre-existing
condition
Adverse drug reaction Possible
adverse drug reaction
ADR of
additional drug
Eriksson et al., Drug Safety, 2014
Drug introduction Drug discontinuationAdverse eventIdentification start
Adverse eventNegative modifier Indication Pre-existing
condition
Adverse drug reaction Possible
adverse drug reaction
ADR of
additional drug
Eriksson et al., Drug Safety, 2014
Drug introduction Drug discontinuation
Adverse eventNegative modifier Indication Pre-existing
condition
Adverse drug reaction Possible
adverse drug reaction
Adverse event
ADR of
additional drug
Identification start
Eriksson et al., Drug Safety, 2014
Drug introduction Drug discontinuation
Adverse eventNegative modifier Indication Pre-existing
condition
Adverse drug reaction Possible
adverse drug reaction
Adverse event
ADR of
additional drug
Identification start
recall known ADRs
estimate ADR frequencies
Eriksson et al., Drug Safety, 2014
discover new ADRs
Acknowledgments
Disease trajectories
Anders Bøck Jensen
Tudor Oprea
Pope Moseley
Søren Brunak
Adverse drug reactions
Robert Eriksson
Thomas Werge
Søren Brunak
EHR text mining
Peter Bjødstrup
Jensen
Robert Eriksson
Henriette Schmock
Francisco S. Roque
Anders Juul
Marlene Dalgaard
Massimo Andreatta
Sune Frankild
Eva Roitmann
Thomas Hansen
Karen Søeby
Søren Bredkjær
Thomas Werge
Søren Brunak
Medical data and text mining: Linking diseases, drugs, and adverse reactions

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Medical data and text mining: Linking diseases, drugs, and adverse reactions