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

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Lars Juhl Jensen
Lars Juhl Jensen

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

Science
1 of 101
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
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