Relating Subjective and Objective Pharmacovigilance Association Measures - Clustering Challenges in Biological Network - page 303

signing drugs as suspect or concomitant, one that will yield assignments in better
general agreement with objective association measures like those considered here.

References

[1] N. Bolshakova and F. Azuaje. Cluster validation techniques for genome expression

data. Signal Processing , 83: 825-833, 2003.

[2] W. DuMouchel. Bayesian data mining in large frequency tables, with an application

to the FDA spontaneous reporting system. American Statistician , 53: 177-190, 1999.

[3] W. DuMouchel and D. Pregibon. Empirical Bayes screening for multi item asso-

ciations. Proc. 7th ACM SIGKDD International Conf. Knowledge Discovery Data
Mining , pages 177-190, 2001.

[4] S. J. W. Evans, P. C. Waller, and S. Davis. Use of proportional reporting ratios (PRRs)

for signal generation from spontaneous adverse drug reaction reports. Pharmacoepi-
demiology Drug Safety , 10: 483-486, 2001.

[5] D. J. Finney. Systemic signalling of adverse reactions to drugs. Methods Inf. Med. ,

13: 1-10, 1974.

[6] D. M. Fram, J. S. Almenoff, and W. DuMouchel. Empirical Bayesian Data Mining

for Discovering Patterns in Post-Marketing Safety Data. Proc. SIGKDD'03 , pages
359-368, 2003.

[7] A. D. Gordon. Classification, 2nd ed. . Chapman and Hall, 1999.

[8] A. L. Gould. Practical pharmacovigilance analysis strategies. Pharmacoepidemiology

Drug Safety , 12: 559-574, 2003.

[9] E. Heeley, L. V. Wilton, and S. A. W. Shakir. Automated Signal Generation in

Prescription-Event Monitoring. Drug Safety , 25: 423-432, 2002.

[10] A. M. Hochberg, S. J. Reisinger, R. K. Pearson, D. J. O'Hara, and K. Hall. Using

data mining to predict safety actions from FDA adverse event reporting system data.
Drug Information Journal , 41: 633-643, 2007.

[11] N. L. Johnson, S. Kotz, and A. W. Kemp. Univariate Discrete Distributions, 2nd ed. ,

Wiley, 1993.

[12] L. Kaufman and P. J. Rousseeuw. Finding Groups in Data . Wiley, 1990.

[13] M. Mammadov and A. Banerjee. An optimization approach to identifying drugs re-

sponsible for adverse drug reactions. Proc. 16th Australasian Workshop Combinato-
rial Algorithms , pages 185-200, 2005.

[14] M. Mammadov and A. Banerjee. An optimization approach to the study of drug-drug

interactions. Proc. 16th Australasian Workshop Combinatorial Algorithms , pages
201-216, 2005.

[15] M. Mammadov, A. Rubinov, and J. Yearwood. The study of drug-reaction relation-

ships using global optimization techniques. Optimization Methods and Software , 22:
99-126, 2007.

[16] R. K. Pearson, T. Zylkin, J. S. Schwaber, and G. E. Gonye. Quantitative evaluation

of clustering results using computational negative controls. Proc. 4th SIAM Interna-
tional Conf. Data Mining , Lake Buena Vista, FL, pages 188-199, April, 2004.

[17] E. P. van Puijenbroek, A. Bate, H. G. M. Leufkens, M. Lindquist, R. Orre, and A.

C. G. Egberts. A comparison of measures of disproportionality for signal detection