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Lars Juhl Jensen jensenlab.org Disease network mining

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Page 1: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

Lars Juhl Jensen jensenlab.org

Disease network mining

Page 2: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

structured data

Page 3: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

Jensen et al., Nature Reviews Genetics, 2012

Page 4: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

unstructured data

Page 5: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

Page 6: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

free text

Page 7: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

Danish

Page 8: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

busy doctors

Page 9: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

typos

Page 10: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

unnatural language

Page 11: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

central registries

Page 12: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

civil registration system

Page 13: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

Jensen et al., Nature Reviews Genetics, 2012

Page 14: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

national discharge registry

Page 15: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

Jensen et al., Nature Reviews Genetics, 2012

Page 16: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

19 years

Page 17: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

6.6 million patients

Page 18: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

163 million diagnoses

Page 19: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

only hospitals

Page 20: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

reimbursement

Page 21: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

linking diseases!

Page 22: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

comorbidity

Page 23: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

contingency table

Page 24: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

Jensen et al., Nature Reviews Genetics, 2012

Page 25: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

confounding factors

Page 26: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

“known knowns”

Page 27: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

sex

Page 28: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

age

Page 29: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

type of hospital encounter

Page 30: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

Jensen et al., Nature Communications, 2014

Page 31: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

“known unknowns”

Page 32: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

smoking

Page 33: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

diet

Page 34: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

“unknown unknowns”

Page 35: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

reporting biases

Page 36: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

disease trajectories!

Page 37: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

temporal correlations

Page 38: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

trajectories

Page 39: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

directional network

Page 40: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

Jensen et al., Nature Communications, 2014

Page 41: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

global map of diseases

Page 42: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

Jensen et al., Nature Communications, 2014

Page 43: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

targeted trajectories

Page 44: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

sepsis

Page 45: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

stratify patients

Page 46: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

diabetes-related sepsis

Page 47: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

Beck et al., Scientific Reports, 2016

Page 48: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

alcohol-related sepsis

Page 49: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

Beck et al., Scientific Reports, 2016

Page 50: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

predict mortality

Page 51: Disease network mining · Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 Patient 6 Patient 7 Patient 8 Patient g Assigned diagnosis Medications Ml M2 M3 Laboratory values

Acknowledgments!Anders Bøck Jensen Mette Kristina Beck

Annelaura Bach Nielsen Anders Perner Tudor Oprea

Pope Moseley Søren Brunak

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