Open AccessJournal Article
Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Philippe Besnard,Steve Hanks +1 more
TLDR
This is the Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence, which was held in Montreal, QU, August 18-20, 1995.Abstract:
This is the Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence, which was held in Montreal, QU, August 18-20, 1995read more
Citations
More filters
Journal ArticleDOI
Comparative study of classification algorithms for immunosignaturing data
TL;DR: ‘Naïve Bayes’ algorithm appears to accommodate the complex patterns hidden within multilayered immunosignaturing microarray data due to its fundamental mathematical properties.
Journal ArticleDOI
Texture analysis in gel electrophoresis images using an integrative kernel-based approach
Carlos Fernandez-Lozano,Jose A. Seoane,Jose A. Seoane,Marcos Gestal,Tom R. Gaunt,Julián Dorado,Alejandro Pazos,Colin Campbell +7 more
TL;DR: FSMKL, a data integration method using multiple kernel learning, which achieved AUROC values above 95% while using a reduced number of features is found, which exhibited the highest discriminating power.
Posted Content
Network analysis of named entity interactions in written texts
TL;DR: A model that links entities appearing in the same context in order to capture the complexity of entities organization through a networked representation is introduced and could be useful to improve the characterization written texts when combined with other traditional approaches based on statistical and deeper paradigms.
Proceedings ArticleDOI
Robust belief roadmap: Planning under uncertain and intermittent sensing
TL;DR: It is shown that it is possible to obtain an analytical bound on the performance of a state estimator under sensor misdetection (intermittency) occurring stochastically over time and this bound is used in a sample-based path planning algorithm to produce a path that trades off accuracy and robustness.
Journal ArticleDOI
Prediction of Anal Cancer Recurrence After Chemoradiotherapy Using Quantitative Image Features Extracted From Serial 18F-FDG PET/CT.
Jiahui Wang,Hao Zhang,Michael D. Chuong,Michael D. Chuong,Kujtim Latifi,Shan Tan,Shan Tan,Wookjin Choi,Wookjin Choi,Sarah E. Hoffe,Ravi Shridhar,Wei Lu,Wei Lu +12 more
TL;DR: The experimental results demonstrated the potential of serial PET/CT scans in early prediction of anal tumor recurrence and employed univariate logistic regression model, multivariate model, and naïve Bayesian classifier to analyze the image features and identify useful tumor recurrent predictors.
References
More filters
Journal ArticleDOI
Comparative study of classification algorithms for immunosignaturing data
TL;DR: ‘Naïve Bayes’ algorithm appears to accommodate the complex patterns hidden within multilayered immunosignaturing microarray data due to its fundamental mathematical properties.
Journal ArticleDOI
Texture analysis in gel electrophoresis images using an integrative kernel-based approach
Carlos Fernandez-Lozano,Jose A. Seoane,Jose A. Seoane,Marcos Gestal,Tom R. Gaunt,Julián Dorado,Alejandro Pazos,Colin Campbell +7 more
TL;DR: FSMKL, a data integration method using multiple kernel learning, which achieved AUROC values above 95% while using a reduced number of features is found, which exhibited the highest discriminating power.
Posted Content
Network analysis of named entity interactions in written texts
TL;DR: A model that links entities appearing in the same context in order to capture the complexity of entities organization through a networked representation is introduced and could be useful to improve the characterization written texts when combined with other traditional approaches based on statistical and deeper paradigms.
Proceedings ArticleDOI
Robust belief roadmap: Planning under uncertain and intermittent sensing
TL;DR: It is shown that it is possible to obtain an analytical bound on the performance of a state estimator under sensor misdetection (intermittency) occurring stochastically over time and this bound is used in a sample-based path planning algorithm to produce a path that trades off accuracy and robustness.
Journal ArticleDOI
Prediction of Anal Cancer Recurrence After Chemoradiotherapy Using Quantitative Image Features Extracted From Serial 18F-FDG PET/CT.
Jiahui Wang,Hao Zhang,Michael D. Chuong,Michael D. Chuong,Kujtim Latifi,Shan Tan,Shan Tan,Wookjin Choi,Wookjin Choi,Sarah E. Hoffe,Ravi Shridhar,Wei Lu,Wei Lu +12 more
TL;DR: The experimental results demonstrated the potential of serial PET/CT scans in early prediction of anal tumor recurrence and employed univariate logistic regression model, multivariate model, and naïve Bayesian classifier to analyze the image features and identify useful tumor recurrent predictors.