Medical data and text mining: Linking diseases, drugs, and adverse reactions
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This document discusses medical data and text mining to link diseases, drugs, and adverse reactions. It describes using structured data from Danish central registries and unstructured data from hospital electronic health records. Named entity recognition is used to extract diseases, drugs, and adverse reactions from free text clinical notes written in Danish. Hand-crafted rules are developed to identify relationships between extracted entities like adverse drug reactions. This allows estimating frequencies of known adverse drug reactions and discovering new adverse drug reactions by analyzing diagnosis trajectories and medication information.
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Medical data and text mining: Linking diseases, drugs, and adverse reactions
- 1. Medical data and text mining Linking diseases, drugs, and adverse reactions Lars Juhl Jensen
- 3. Jensen et al., Nature Reviews Genetics, 2012
- 9. opt-out
- 10. opt-in
- 11. registry data
- 14. CPR number
- 15. Jensen et al., Nature Reviews Genetics, 2012
- 17. 14 years
- 22. ICD-10
- 23. Jensen et al., Nature Reviews Genetics, 2012
- 24. not research
- 25. reimbursement
- 27. comorbidity
- 29. Jensen et al., Nature Reviews Genetics, 2012
- 31. “known knowns”
- 32. gender
- 33. age
- 34. type of hospital encounter
- 35. Jensen et al., Nature Communications, 2014
- 36. “known unknowns”
- 37. smoking
- 38. diet
- 40. reporting biases
- 41. matched controls
- 42. proxy diagnoses
- 45. Jensen et al., Nature Communications, 2014
- 47. Jensen et al., Nature Communications, 2014
- 48. key diagnoses
- 49. Jensen et al., Nature Communications, 2014
- 51. clinical text
- 54. free text
- 55. Danish
- 57. busy doctors
- 58. abbreviations
- 59. misspellings
- 60. too much to read
- 61. computer
- 62. as smart as a dog
- 63. teach it specific tricks
- 68. diseases
- 69. drugs
- 71. synonyms
- 75. expansion rules
- 77. Clozapine
- 79. “black list”
- 82. clinical trials
- 85. underreporting
- 86. text/data mining
- 87. medication
- 88. Jensen et al., Nature Reviews Genetics, 2012
- 89. adverse events
- 92. 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
- 93. 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
- 94. 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
- 95. 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
- 98. Eriksson et al., Drug Safety, 2014
- 100. 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