Medical data mining

1,336 views

Published on

Published in: Technology, Health & Medicine
0 Comments
2 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
1,336
On SlideShare
0
From Embeds
0
Number of Embeds
9
Actions
Shares
0
Downloads
20
Comments
0
Likes
2
Embeds 0
No embeds

No notes for slide

Medical data mining

  1. 1. Medical data mining Linking diseases, drugs, and adverse reactions Lars Juhl Jensen
  2. 2. unstructured data
  3. 3. structured data
  4. 4. Jensen et al., Nature Reviews Genetics, 2012
  5. 5. individual hospitals
  6. 6. central registries
  7. 7. opt-out
  8. 8. opt-in
  9. 9. Danish registries
  10. 10. civil registration system
  11. 11. CPR number
  12. 12. established in 1968
  13. 13. Jensen et al., Nature Reviews Genetics, 2012
  14. 14. national discharge registry
  15. 15. 14 years
  16. 16. 6.2 million patients
  17. 17. 45 million admissions
  18. 18. 68 million records
  19. 19. 119 million diagnosis
  20. 20. ICD-10
  21. 21. Jensen et al., Nature Reviews Genetics, 2012
  22. 22. reimbursement
  23. 23. not research
  24. 24. diagnosis trajectories
  25. 25. naïve approach
  26. 26. comorbidity
  27. 27. Jensen et al., Nature Reviews Genetics, 2012
  28. 28. confounding factors
  29. 29. “known knowns”
  30. 30. gender
  31. 31. age
  32. 32. type of hospital encounter
  33. 33. Male Emergency room Out-patient In-patient Female Jensen et al., submitted, 2013
  34. 34. “known unknowns”
  35. 35. smoking
  36. 36. diet
  37. 37. “unknown unknowns”
  38. 38. reporting biases
  39. 39. disease clustering
  40. 40. temporal correlation
  41. 41. Jensen et al., submitted, 2013
  42. 42. diagnosis trajectories
  43. 43. Jensen et al., submitted, 2013
  44. 44. epilepsy
  45. 45. Jensen et al., submitted, 2013
  46. 46. gout
  47. 47. Jensen et al., submitted, 2013
  48. 48. electronic health records
  49. 49. structured data
  50. 50. Jensen et al., Nature Reviews Genetics, 2012
  51. 51. unstructured data
  52. 52. free text
  53. 53. Danish
  54. 54. busy doctors
  55. 55. psychiatric patients
  56. 56. delusions
  57. 57. text mining
  58. 58. named entity recognition
  59. 59. custom dictionaries
  60. 60. diseases
  61. 61. drugs
  62. 62. adverse drug events
  63. 63. expansion rules
  64. 64. orthographic variation
  65. 65. typos
  66. 66. “negative modifiers”
  67. 67. negations
  68. 68. family members
  69. 69. detailed disease profiles
  70. 70. Text mined codes Assigned codes 4947 3825 32626 Roque et al., PLOS Computational Biology, 2011
  71. 71. comorbidity
  72. 72. Roque et al., PLOS Computational Biology, 2011
  73. 73. patient stratification
  74. 74. Roque et al., PLOS Computational Biology, 2011
  75. 75. cluster characterization
  76. 76. Roque et al., PLOS Computational Biology, 2011
  77. 77. adverse drug reactions
  78. 78. structured data
  79. 79. medication
  80. 80. clinical narrative
  81. 81. possible ADRs
  82. 82. semi-structured data
  83. 83. SPC Summary of Product Characteristics
  84. 84. drug indications
  85. 85. known ADRs
  86. 86. temporal correlation
  87. 87. link drugs to ADRs
  88. 88. complex filtering
  89. 89. Eriksson et al., submitted, 2013
  90. 90. new ADRs
  91. 91. Drug substance ADE Chlordiazepoxide Nystagmus Simvastatin Personality changes Dipyridamole Visual impairment Citalopram Psychosis Bendroflumethiazi Apoplexy de p-value 4.0e-8 8.4e-8 4.4e-4 8.8e-4 8.5e-3 Eriksson et al., submitted, 2013
  92. 92. ADR frequencies
  93. 93. Eriksson et al., submitted, 2013
  94. 94. heavily medicated
  95. 95. Eriksson et al., submitted, 2013
  96. 96. ADR dose dependency
  97. 97. Eriksson et al., submitted, 2013
  98. 98. ADR similarity
  99. 99. Eriksson et al., submitted, 2013
  100. 100. drug repurposing
  101. 101. Campillos, Kuhn et al., Science, 2008
  102. 102. Acknowledgments 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 Disease trajectories Anders Bøck Jensen Tudor Oprea Pope Moseley Søren Brunak Adverse drug reactions Robert Eriksson Thomas Werge Søren Brunak
  103. 103. Thank you!

×