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Mining literature and medical records Lars Juhl Jensen
literature mining
exponential growth
 
 
some things are constant
 
~45 seconds per paper
computer
as smart as a dog
teach it specific tricks
 
 
named entity recognition
comprehensive lexicon
orthographic variation
“ black list”
Reflect.ws
augmented browsing
Pafilis, O’Donoghue, Jensen et al.,  Nature Biotechnology , 2009 O’Donoghue et al.,  Journal of Web Semantics , 2010
small molecules
proteins
subcellular compartments
tissues
diseases
information extraction
no access
 
collaboration
 
medical record mining
electronic patient journals
psychiatric diseases
F20 F200 Negation Family
domain specific
patient stratification
 
 
comorbidity matrix
 
detailed phenotype data
thousands of individuals
coarse phenotype data
millions of patients
national discharge registry
6.2 million individuals
66 million admissions
119 million diagnoses
comorbidity matrix
confounding factors
gender
age
obesity
smoking
thousands of known links
surprising comorbidities
embedded/impacted tooth
neoplasms in oral cavity
reporting bias
predict future diseases
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Thank you!
larsjuhljensen

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