C4.5: programs for machine learning
C4.5: programs for machine learning
IEEE Transactions on Pattern Analysis and Machine Intelligence
ASSERT: a physician-in-the-loop content-based retrieval system for HRCT image databases
Computer Vision and Image Understanding - Special issue on content-based access for image and video libraries
Use of Contextual Information for Feature Ranking and Discretization
IEEE Transactions on Knowledge and Data Engineering
Machine Learning
SSPR '96 Proceedings of the 6th International Workshop on Advances in Structural and Syntactical Pattern Recognition
Ensemble Methods in Machine Learning
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Classifier Combinations: Implementations and Theoretical Issues
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Combining Textual and Visual Cues for Content-Based Image Retrieval on the World Wide Web
CBAIVL '98 Proceedings of the IEEE Workshop on Content - Based Access of Image and Video Libraries
PCA-based Feature Transformation for Classification: Issues in Medical Diagnostics
CBMS '04 Proceedings of the 17th IEEE Symposium on Computer-Based Medical Systems
Probability Estimates for Multi-class Classification by Pairwise Coupling
The Journal of Machine Learning Research
Optimal multimodal fusion for multimedia data analysis
Proceedings of the 12th annual ACM international conference on Multimedia
Early versus late fusion in semantic video analysis
Proceedings of the 13th annual ACM international conference on Multimedia
Early versus late fusion in semantic video analysis
Proceedings of the 13th annual ACM international conference on Multimedia
Learning from imbalanced data in surveillance of nosocomial infection
Artificial Intelligence in Medicine
Classifier fusion: combination methods for semantic indexing in video content
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Combining feature subsets in feature selection
MCS'05 Proceedings of the 6th international conference on Multiple Classifier Systems
Isotropic polyharmonic B-splines: scaling functions and wavelets
IEEE Transactions on Image Processing
Medical image retrieval and automated annotation: OHSU at ImageCLEF 2006
CLEF'06 Proceedings of the 7th international conference on Cross-Language Evaluation Forum: evaluation of multilingual and multi-modal information retrieval
Inter-media concept-based medical image indexing and retrieval With UMLS at IPAL
CLEF'06 Proceedings of the 7th international conference on Cross-Language Evaluation Forum: evaluation of multilingual and multi-modal information retrieval
Guest editorial: Knowledge discovery and computer-based decision support in biomedicine
Artificial Intelligence in Medicine
Fast fractal stack: fractal analysis of computed tomography scans of the lung
MMAR '11 Proceedings of the 2011 international ACM workshop on Medical multimedia analysis and retrieval
3D case–based retrieval for interstitial lung diseases
MCBR-CDS'09 Proceedings of the First MICCAI international conference on Medical Content-Based Retrieval for Clinical Decision Support
Transductive cost-sensitive lung cancer image classification
Applied Intelligence
Retrieval of high-dimensional visual data: current state, trends and challenges ahead
Multimedia Tools and Applications
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Objective: We investigate the influence of the clinical context of high-resolution computed tomography (HRCT) images of the chest on tissue classification. Methods and materials: 2D regions of interest in HRCT axial slices from patients affected with an interstitial lung disease are automatically classified into five classes of lung tissue. Relevance of the clinical parameters is studied before fusing them with visual attributes. Two multimedia fusion techniques are compared: early versus late fusion. Early fusion concatenates features in one single vector, yielding a true multimedia feature space. Late fusion consisting of the combination of the probability outputs of two support vector machines. Results and conclusion: The late fusion scheme allowed a maximum of 84% correct predictions of testing instances among the five classes of lung tissue. This represents a significant improvement of 10% compared to a pure visual-based classification. Moreover, the late fusion scheme showed high robustness to the number of clinical parameters used, which suggests that it is appropriate for mining clinical attributes with missing values in clinical routine.