Modeling fMRI data generated by overlapping cognitive processes with unknown onsets using Hidden Process Models.
NeuroImage, 2009
Finding a Haystack in Haystacks - Simultaneous Identification of Concepts in Large Bio-Medical Corpora.
Proceedings of the SIAM International Conference on Data Mining, 2008
Large Scale Diagnostic Code Classification for Medical Patient Records.
Proceedings of the Third International Joint Conference on Natural Language Processing, 2008
Real-time data pre-processing technique for efficient feature extraction in large scale datasets.
Proceedings of the 17th ACM Conference on Information and Knowledge Management, 2008
Block-Suffix Shifting: Fast, Simultaneous Medical Concept Set Identification in Large Medical Record Corpora.
Proceedings of the AMIA 2008, 2008
Federated Ontology Search for the Medical Domain.
Proceedings of the On the Move to Meaningful Internet Systems 2007: OTM 2007 Workshops, 2007
A Theoretical Framework for Learning Bayesian Networks with Parameter Inequality Constraints.
Proceedings of the IJCAI 2007, 2007
Automatic medical coding of patient records via weighted ridge regression.
Proceedings of the Sixth International Conference on Machine Learning and Applications, 2007
Modeling the fMRI Signal via Hierarchical Clustered Hidden Process Models.
Proceedings of the AMIA 2007, 2007
Data mining for improved cardiac care.
SIGKDD Explor., 2006
Bayesian Network Learning with Parameter Constraints.
J. Mach. Learn. Res., 2006
Exploiting Parameter Related Domain Knowledge for Learning in Graphical Models.
Proceedings of the 2005 SIAM International Conference on Data Mining, 2005
Learning to Decode Cognitive States from Brain Images.
Mach. Learn., 2004
Clinical and financial outcomes analysis with existing hospital patient records.
Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 24, 2003
Classifying Instantaneous Cognitive States from fMRI Data.
Proceedings of the AMIA 2003, 2003
Evaluating the C-section Rate of Different Physician Practices: Using Machine Learning to Model Standard Practice.
Proceedings of the AMIA 2003, 2003
Mining time-dependent patient outcomes from hospital patient records.
Proceedings of the AMIA 2002, 2002
Machine learning for sub-population assessment: evaluating the C-section rate of different physician practices.
Proceedings of the AMIA 2002, 2002
Some results on the Collatz problem.
Acta Informatica, 2000