A method for mining infrequent causal associations and its application in finding adverse drug reaction signal pairs

IEEE Transactions on Knowledge and Data Engineering

Volumn 25, Issue 4, 2013, Pages 721-733

  Ji, Yanqing ^a   Ying, Hao ^b   Tran, John ^c   Dews, Peter ^d   Mansour, Ayman ^b   Michael Massanari, R ^e  

^a GONZAGA UNIVERSITY   (United States)

^b Wayne State University   (United States)

^c Spokane Mental Health   (United States)

^d ST MARY MERCY HOSPITAL   (United States)

^e Critical Junctures Institute   (United States)

Author keywords

Adverse drug reactions; association rules; data mining algorithms; interestingness measure; recognition primed decision model

Indexed keywords

ADVERSE DRUG REACTION (ADRS); ADVERSE DRUG REACTIONS; CAUSAL RELATIONSHIPS; DATA MINING ALGORITHM; DATA MINING FRAMEWORKS; DECISION MODELS; DETROIT; DRUG SAFETY; ENALAPRIL; EVENT PATTERN; INTERESTINGNESS MEASURES; ITS APPLICATIONS; LOW PROBABILITY; MEDICAL CENTER; MICHIGAN; PATIENT DATA; PRAVASTATIN; PROJECT TEAM; REAL-WORLD APPLICATION;

ALGORITHMS; ASSOCIATION RULES; DATA MINING; HOSPITAL DATA PROCESSING;

PHARMACODYNAMICS;

EID: 84874596859     PISSN: 10414347     EISSN: None     Source Type: Journal    
DOI: 10.1109/TKDE.2012.28     Document Type: Article

References (54)

1. J. Talbot and P. Waller, Stephens' Detection of New Adverse Drug Reactions, fifth ed. John Wiley & Sons, 2004.
2. L.T. Kohn, J.M. Corrigan, and M.S. Donaldson, To Error is Human: Building a Safer Health System. Nat'l Academy Press, 2000.
3. J. Lazarou, B.H. Pomeranz, and P.N. Corey, "Incidence of Adverse Drug Reactions in Hospitalized Patients: A Meta-Analysis of Prospective Studies," J. Am. Medical Assoc., vol. 279, pp. 1200-1205, Apr. 1998. (Pubitemid 28193431)
4. K. Hartmann, A.K. Doser, and M. Kuhn, "Postmarketing Safety Information: How Useful are Spontaneous Reports?," Pharmacoe-pidemiology and Drug Safety, vol. 8, pp. 65-71, 1999.
5. L. Hazell and S.A.W. Shakir, "Under-Reporting of Adverse Drug Reactions-A Systematic Review," Drug Safety, vol. 29, pp. 385-396, 2006.
6. K.E. Lasser, P.D. Allen, S.J. Woolhandler, D.U. Himmelstein, S.M. Wolfe, and D.H. Bor, "Timing of New Black Box Warnings and Withdrawals for Prescription Medications," J. Am. Medical Assoc., vol. 287, pp. 2215-2220, 2002. (Pubitemid 34441937)
7. A. Szarfman, J.M. Tonning, and P.M. Doraiswamy, "Pharmacov-igilance in the 21st Century: New Systematic Tools for an Old Problem," Pharmacotherapy, vol. 24, pp. 1099-1104, 2004. (Pubitemid 39128833)
8. M. Lindquist, I.R. Edwards, A. Bate, H. Fucik, A.M. Nunes, and M. Stahl, "From Association to Alert-a Revised Approach to International Signal Analysis," Pharmacoepidemiology and Drug Safety, vol. 1, pp. 15-25, 1999.
9. S.J. Evans, P.C. Waller, and S. Davis, "Use of Proportional Reporting Ratios (PRRs) for Signal Generation from Spontaneous Adverse Drug Reaction Reports," Pharmacoepidemiology and Drug Safety, vol. 10, pp. 483-486, 2001. (Pubitemid 34100774)
10. W. DuMouchel, "Bayesian Data Mining in Large Frequency Tables, with an Application to the FDA Spontaneous Reporting System," Am. Statistician, vol. 53, pp. 177-190, 1999.
11. P. Purcell and S. Barty, "Statistical Techniques for Signal Generation: The Australian Experience," Drug Safety, vol. 25, pp. 415-421, 2002. (Pubitemid 34729140)
12. M. Hauben, "Early Postmarketing Drug Safety Surveillance: Data Mining Points to Consider," Ann. of Pharmacotherapy, vol. 38, pp. 1625-1630, Oct. 2004. (Pubitemid 39297758)
13. Y. Ji, H. Ying, M.S. Farber, J. Yen, P. Dews, R.E. Miller, and R.M. Massanari, "A Distributed, Collaborative Intelligent Agent System Approach for Proactive Postmarketing Drug Safety Surveillance," IEEE Trans. Information Technology in Biomedicine, vol. 14, no. 3, pp. 826-837, Dec. 2010.
14. H. Jin, J. Chen, H. He, G. Williams, C. Kelman, and C. O'Keefe, "Mining Unexpected Temporal Associations: Applications in Detecting Adverse Drug Reactions," IEEE Trans. Information Technology in Biomedicine, vol. 12, no. 4, pp. 488-500, July 2008.
15. G.N. Norén, J. Hopstadius, A. Bate, K. Star, and I.R. Edwards, "Temporal Pattern Discovery in Longitudinal Electronic Patient Records" Data Mining and Knowledge Discovery, vol. 20, pp. 361-387, 2010.
16. Y. Ji, H. Ying, P. Dews, M.S. Farber, A. Mansour, J. Tran, R.E. Miller, and R.M. Massanari, "A Fuzzy Recognition-Primed Decision Model-Based Causal Association Mining Algorithm for Detecting Adverse Drug Reactions in Postmarketing Surveillance," Proc. IEEE Int'l Conf. Fuzzy Systems, 2010.
17. Y. Ji, H. Ying, P. Dews, A. Mansour, J. Tran, R.E. Miller, and R.M. Massanari, "A Potential Causal Association Mining Algorithm for Screening Adverse Drug Reactions in Postmarketing Surveillance," IEEE Trans. Information Technology in Biomedicine, vol. 15, no. 32, pp. 428-437, May 2011.
18. Y. Ji, R.M. Massanari, J. Ager, J. Yen, R.E. Miller, and H. Ying, "A Fuzzy Logic-Based Computational Recognition-Primed Decision Model," Information Science, vol. 177, pp. 4338-4353, 2007. (Pubitemid 47071911)
19. P.-N. Tan, M. Steinbach, and V. Kumar, Introduction to Data Mining. Addison-Wesley, 2005.
20. L. Geng and H.J. Hamilton, "Interestingness Measures for Data Mining: A Survey," ACM Computing Surverys, vol. 38, no. 3, article 9, 2006.
21. A.K.H. Tung, H. Lu, J. Han, and L. Feng, "Efficient Mining of Intertransaction Association Rules," IEEE Trans. Knowledge and Data Eng., vol. 15, no. 1, pp. 43-56, Jan./Feb. 2003.
22. C. Marinica and F. Guillet, "Knowledge-Based Interactive Post-mining of Association Rules Using Ontologies," IEEE Trans. Knowledge and Data Eng., vol. 22, no. 6, pp. 784-797, June 2010.
23. R. Agrawal and R. Sreikant, "Fast Algorithms for Mining Association Rules," Proc. 20th Int'l Conf. Very Large Databases, 1994.
24. P.-N. Tan and V. Kumar, "Interestingness Measures for Association Patterns : A Perspective," Department of Computer Science, Univ. of Minnesota, 2000.
25. W. Klosgen, "Explora: A Multipattern and Multistrategy Discovery Assistant," Advances in Knowledge Discovery and Data Mining, U.M. Fayyad, et al., eds., first ed., MIT Press, pp. 249-271, 1996.
26. N. Lavrac, P. Flach, and B. Zupan, "Rule Evaluation Measures: A Unifying View," Proc. Ninth Int'l Workshop Inductive Logic Programming, 1999.
27. G.M. Weiss, "Mining with Rarity: A Unifying Framework," ACM SIGKDD Explorations Newsletter, vol. 6, pp. 7-19, 2004.
28. B. Liu, W. Hsu, and Y. Ma, "Mining Association Rules with Multiple Minimum Supports," Proc. Fifth ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining, 1999.
29. H. Yun, D. Ha, B. Hwang, and K.H. Ryu, "Mining Association Rules on Significant Rare Data Using Relative Support," J. Systems Software, vol. 67, pp. 181-191, 2003.
30. Y.-H. Hu and Y.-L. Chen, "Mining Association Rules with Multiple Minimum Supports: A New Mining Algorithm and a Support Tuning Mechanism," Decision Support Systems, vol. 42, pp. 1-24, 2006. (Pubitemid 44278264)
31. L. Szathmary, P. Valtchev, and A. Napoli, "Finding Minimal Rare Itemsets and Rare Association Rules," Proc. Fourth Int'l Conf. Knowledge Science, Eng. and Management, pp. 16-27, 2010.
32. L. Szathmary, A. Napoli, and P. Valtchev, "Towards Rare Itemset Mining," Proc IEEE 19th Int'l Conf. Tools with Artificial Intelligence, 2007.
33. L. Troiano, G. Scibelli, and C. Birtolo, "A Fast Algorithm for Mining Rare Itemsets," Proc. Ninth Int'l Conf. Intelligent Systems Design and Applications, 2009.
34. Y.S. Koh and N. Rountree, "Finding Sporadic Rules Using Apriori-Inverse," Advances in Knowledge Discovery and Data Mining, vol. 3518, pp. 97-106, 2005.
35. M. Adda, L. Wu, and Y. Feng, "Rare Itemset Mining," Proc. Sixth Int'l Conf. Machine Learning and Applications, pp. 73-80, 2007.
36. C. Zhang and S. Zhang, Association Rule Mining: Models and Algorithms. Springer-Verlag, 2002.
37. I. Guyon, D. Janzing, and B. Schölkopf, "Causality: Objectives and Assessment," JMLR Machine Learning Research Workshop and Conf. Proc., vol. 6, pp. 1-42, 2010.
38. J. Pearl, Causality: Models, Reasoning and Inference, second ed. Cambridge Univ. Press, 2009.
39. C. Silverstein, S. Brin, R. Motwani, and J. Ullman, "Scalable Techniques for Mining Causal Structures," Data Mining and Knowledge Discovery, vol. 4, pp. 163-192, 2000.
40. M. Hassoun, Fundamentals of Artificial Neural Networks. The MIT Press, 2003.
41. G.A. Fink, Markov Models for Pattern Recognition: From Theory to Applications. Springer, 2010.
42. D. Heckerman, "Bayesian Networks for Data Mining," Data Mining Knowledge Discovery, vol. 1, pp. 79-119, 1997. (Pubitemid 127721237)
43. G.F. Cooper, "A Simple Constraint-Based Algorithm for Efficiently Mining Observational Databases for Causal Relationships," Data Mining Knowledge Discovery, vol. 1, pp. 203-224, 1997.
44. A. Krogh, M. Brown, I.S. Mian, K. Sjolander, and D. Haussler, "Hidden Markov Models in Computational biology. Applications to Protein Modeling," J. Molecular Biology, vol. 235, pp. 1501-1531, 1994.
45. S.R. Eddy, "Profile Hidden Markov Models," Bioinformatics, vol. 14, pp. 755-763, 1998. (Pubitemid 28552108)
46. G.A. Klein, "A Recognition-Primed Decision Making Model of Rapid Decision Making," Decision Making in Action: Models and Methods, pp. 138-147, Ablex Publishing, 1993.
47. L.A. Zadeh, "Fuzzy Sets," Information and Control, vol. 8, pp. 338-353, 1965.
48. H. Ying, Fuzzy Control and Modeling: Analytical Foundations and Applications. IEEE Press, 2000.
49. I.R. Edwards and J.K. Aronson, "Adverse Drug Reactions: Definitions, Diagnosis, and Management," Lancet, vol. 356, pp. 1255-1259, 2000.
50. Y. Ji, H. Ying, J. Yen, and R.M. Massanari, "A Fuzzy Logic-Based Computational Recognition-Primed Decision Model," Information Science, vol. 77, pp. 4338-4353, 2007. (Pubitemid 47071911)
51. M. Cayrol, H. Farreny, and H. Prade, "Fuzzy Pattern-Matching," Kybernetes, vol. 11, pp. 103-116, 1982.
52. R. Orchard, "Fuzzy Reasoning in Jess: The FuzzyJ Toolkit and FuzzyJess," Proc. Third Int'l Conf. Enterprise Information Systems, pp. 533-542, 2001.
53. P. Staff, Physicians' Desk Reference 2011. PDR Network, 2010.
54. M. Hauben and X. Zhou, "Quantitative Methods in Pharmacov-igilance: Focus on Signal Detection," Drug Safety, vol. 26, pp. 159-186, 2003. (Pubitemid 36308102)