Publications

Links in italics are password protected.

36

Roland Orre.
IT-situationen för gymnasieskolan i Solna.
Tech. Rep. NL-2010-01, NeuroLogic Sweden AB, AlbaNova University Center, Stockholm, Sweden, 2010.
abstract, pdf.

35

Gauthier Descamps.
Concept Wish-IT®, conception produit réalisé par le client.
Master's thesis, ESPEME, Stockholm, March 2009, performed at NeuroLogic Sweden AB, Stockholm.

34

Thomas Trinché.
Research and development of a simulator and a clustering method based upon artificial neural networks.
Master's thesis, 3iL, Stockholm, Aug 2008, performed at NeuroLogic Sweden AB, Stockholm.

33

Sylvain Brau.
Design and implementation of Wish-IT® search engine prototype.
Master's thesis, Universite Joseph Fourier, Linköping-Stockholm, Aug 2007, performed at NeuroLogic Sweden AB, Stockholm.

32

G. Niklas Norén, Roland Orre, Andrew Bate, and I. Ralph Edwards.
Duplicate detection in adverse reaction surveillance.
Data Mining and Knowledge Discovery, 14(3):305-328, June 2007.
abstract, pdf, publisher site.

31

Ludovic Roguet.
Design and implementation of a demand driven products search engine.
Master's thesis, Universite Joseph Fourier, Linköping-Stockholm, Aug 2006, performed at NeuroLogic Sweden AB, Stockholm.

30

G. Niklas Norén, Andrew Bate, Roland Orre, and I. Ralph Edwards.
Extending the methods used to screen the WHO drug safety database towards analysis of complex associations and improved accuracy for rare events.
Statistics in Medicine, 25:3740-3757, 2006.
abstract, pdf, ps.

29

G. Niklas Norén, Roland Orre, and Andrew Bate.
A hit-miss model for duplicate detection in the WHO drug safety database.
In Proceedings of the 11th ACM SIGKDD international conference on knowledge discovery and data mining, pages 459-468, Chicago, IL, August 2005. ACM Press.
Won the "Best application paper award" at KDD2005 in Chicago.
abstract, pdf, ps.

28

Roland Orre, Andrew Bate, G. Niklas Norén, Erik Swahn, Stefan Arnborg, and I. Ralph Edwards.
A Bayesian recurrent neural network approach for finding dependencies in large incomplete data sets.
International Journal of Neural Systems, 15(3):207-222, June 2005.
abstract, pdf, ps.

27

G. Niklas Norén and Roland Orre.
Case based imprecision estimates for Bayes classifiers with the Bayesian bootstrap.
Machine Learning, 58:79-94, January 2005.
abstract, Springer Link, ps.

26

Roland Orre.
On Data Mining and Classification Using a Bayesian Confidence Propagation Neural Network.
PhD thesis, Dept. of Numerical Analysis and Computing Science, Royal Institute of Technology, Stockholm, Sweden, August 2003, TRITA-NA-0308.
abstract, pdf, ps.

25

Niklas Norén.
A Monte Carlo method for Bayesian dependency derivation.
Master's thesis, Chalmers University of Technology, Gothenburg, 2002, performed at company NeuroLogic.
abstract, pdf, ps.

24

Andrew Bate, Marie Lindquist, Roland Orre, I. Ralph Edwards, and Ronald H. B. Meyboom.
Data-mining analyses of pharmacovigilance signals in relation to relevant comparision drugs.
European Journal of Clinical Pharmacology, 58(7):483-490, October 2002.
abstract, pdf (site pw).

23

E. M. van Puijenbroek, A. Bate, H. G. M. Leufkens, M. Lindquist, R. Orre, and A. C. G. Egberts.
A comparision of measures of disproportionality for signal detection in spontaneous reporting systems for adverse drug reactions.
Pharmacoepidemiology and Drug Safety, 11(1):3-10, 2002.
abstract, pdf (site pw).

22

A. Bate, R. Orre, M. Lindquist, and I. R. Edwards.
Explanation of data mining methods.
http://bmj.com/cgi/content/full/322/7296/1207/DC1, 2001.
changed to http://bmj.com/content/suppl/2001/05/17/322.7296.1207.DC1, http.

21

Roland Orre, Andrew Bate, Marie Lindquist, and I.R. Edwards.
Recurrent Bayesian neural network applied to finding complex associations in the WHO database of adverse drug reactions.
In Proc. of 22nd Annual Conference of International Society for Clinical Biostatistics, Stockhom, Sweden, August 2001.

20

Roland Orre and Andrew Bate.
Investigating recalled pattern frequencies with a recurrent Bayesian neural network.
Tech. Rep. UMCNL-2001:I1, Dept. of Mathematical Statistics, Stockholm University, Stockholm, Sweden, 2001.

19

Roland Orre and Andrew Bate.
Investigating influence of bias variation on recalled pattern with a recurrent Bayesian neural network.
Tech. Rep. UMCNL-2001:I2, Dept. of Mathematical Statistics, Stockholm University, Stockholm, Sweden, 2001.

18

D. M. Coulter, A. Bate, Ronald H. B. Meyboom, and M. Lindquist I. R. Edwards.
Antipsychotics drugs and heart muscle disorder in international pharmacovigilance: a data mining study.
BMJ, 322:1207-1209, 2001.
abstract, pdf.

17

Roland Orre, Andrew Bate, and Marie Lindquist.
Bayesian neural networks used to find adverse drug related syndromes.
In Proc. of the ANNIMAB-1 Conference, pages 215-220, Gothenburg, Sweden, April 2000. Springer.
abstract, pdf.

16

Roland Orre, Anders Lansner, Andrew Bate, and Marie Lindquist.
Bayesian neural networks with confidence estimations applied to data mining.
Computational Statistics and Data Analysis, 34(4)(4):473-493, 2000.
abstract, pdf, ps.

15

M. Lindquist, M. Ståhl, A. Bate, I.R. Edwards, and Ronald H. B. Meyboom .
A retrospective evaluation of a data mining approach to aid finding new adverse drug reaction signals in the WHO international database.
Drug Safety, 23(6):533-542, 2000.
abstract.

14

M. Lindquist, I. R. Edwards, A. Bate, H. Fucik, A. M. Nunes, and M. Ståhl.
From association to alert - a revised approach to international signal analysis.
Pharmacoepidemiology and Drug Safety, 8(S1):15-25, 1999.
abstract, pdf (site pw).

13

Andrew Bate, Marie Lindquist, I. Ralph Edwards, Sten Olsson, Roland Orre, Anders Lansner, and Rogelio Melhado De Freitas.
A Bayesian neural network method for adverse drug reaction signal generation.
European Journal of Clinical Pharmacology, 54(4):315-321, 1998.
abstract, pdf, publisher site.

12

Andrew Bate, Marie Lindquist, Roland Orre, and Ralph Edwards.
Identifying and quantifying signals automatically.
Pharmacoepidemiology and Drug Safety 1998, 7(S2):99, 1998.

11

Roland Orre.
Data Mining and Process Modelling using a Bayesian Confidence Propagation Neural Network.
Licentiate thesis, Dept. of Numerical Analysis and Computing Science, Royal Institute of Technology, Stockholm, Sweden, June 1998, TRITA-NA-P9810.
abstract, pdf, ps.

10

Timo Koski and Roland Orre.
Statistics of the information component in Bayesian neural networks.
Tech. Rep. TRITA-NA-P9806, Dept. of Numerical Analysis and Computing Science, Royal Institute of Technology, Stockholm, Sweden, 1998.
abstract, pdf, ps.

9

Roland Orre and Anders Lansner.
Pulp quality modelling using Bayesian mixture density neural networks.
Journal of Systems Engineering, 6:128-136, 1996.
abstract, pdf, ps.

8

Roland Orre and Anders Lansner.
Pulp quality modelling using Bayesian mixture density neural networks.
In A. Bulsari and S. Kallio, editors, Engineering Applications of Artificial Neural Networks, pages 351-358, Otaniemi, Finland, August 21-23 1995. Finnish Artificial Intelligence Society.
Proc. EANN-95.
abstract, pdf, ps.

7

Roland Orre and Anders Lansner.
Function approximation by prediction of a posteriori density with Bayesian ann:s.
Tech. Rep. TRITA-NA-P9413, Dept. of Numerical Analysis and Computing Science, Royal Institute of Technology, Stockholm, Sweden, 1994.

6

Roland Orre.
Multi module ANN simulator for MIMD architecture.
In Proc. Mechatronical Computer Systems for Perception and Action, pages 85-88, Halmstad, Sweden, June 1-3 1993.

5

Roland Orre and Anders Lansner.
Process modelling using artificial neural networks.
In Stan Gielen and Bert Kappen, editors, ICANN'93, Proceedings of the International Conference on Artificial Neural Networks, page 862, Amsterdam, September 13-16 1993. Elsevier.

4

Roland Orre and Anders Lansner.
A study of process modelling using artificial neural networks.
Tech. Rep. TRITA-NA-P9239, Dept. of Numerical Analysis and Computing Science, Royal Institute of Technology, Stockholm, Sweden, 1992.

3

Roland Orre and Anders Lansner.
A Bayesian network for temporal segmentation.
In Igor Alexander and John Taylor, editors, Artificial Neural Networks, pages 1081-1084, Amsterdam, September 4-7 1992. Elsevier.
Proc. ICANN'92, Brighton, United Kingdom.
abstract, pdf, ps.

2

Martin Wikström, Roland Orre, and Anders Lansner.
A method for motor learning in artificial neural systems.
In Proc. European Neuroscience Association (ENA) Annual Meeting, 1991.
Cambridge, England.

1

Roland Orre and Anders Lansner.
A method for temporal association in Bayesian networks.
Tech. Rep. TRITA-NA-P9018, Dept. of Numerical Analysis and Computing Science, Royal Institute of Technology, Stockholm, Sweden, 1990.
abstract, pdf, ps.