Machine Learning
A decision-theoretic generalization of on-line learning and an application to boosting
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition, Fourth Edition
Pattern Recognition, Fourth Edition
Journal of Visualization
Neighbor-weighted K-nearest neighbor for unbalanced text corpus
Expert Systems with Applications: An International Journal
An Ordinal Data Method for the Classification with Reject Option
ICMLA '09 Proceedings of the 2009 International Conference on Machine Learning and Applications
Pattern Recognition Letters
Classification of the electrocardiogram signals using supervised classifiers and efficient features
Computer Methods and Programs in Biomedicine
Machine learning of clinical performance in a pancreatic cancer database
Artificial Intelligence in Medicine
Computer Methods and Programs in Biomedicine
A perceptual similarity method by pairwise comparison in a medical image case
Machine Vision and Applications
Diagnostic of pathology on the vertebral column with embedded reject option
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Computer Aided Diagnosis tool for Alzheimer's Disease based on Mann-Whitney-Wilcoxon U-Test
Expert Systems with Applications: An International Journal
Automatic Speech Signal Analysis for Clinical Diagnosis and Assessment of Speech Disorders
Automatic Speech Signal Analysis for Clinical Diagnosis and Assessment of Speech Disorders
A random forest classifier for lymph diseases
Computer Methods and Programs in Biomedicine
A novel method for pulmonary embolism detection in CTA images
Computer Methods and Programs in Biomedicine
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A novel method to classify multi-class biomedical objects is presented. The method is based on a hybrid approach which combines pairwise comparison, Bayesian regression and the k-nearest neighbor technique. It can be applied in a fully automatic way or in a relevance feedback framework. In the latter case, the information obtained from both an expert and the automatic classification is iteratively used to improve the results until a certain accuracy level is achieved, then, the learning process is finished and new classifications can be automatically performed. The method has been applied in two biomedical contexts by following the same cross-validation schemes as in the original studies. The first one refers to cancer diagnosis, leading to an accuracy of 77.35% versus 66.37%, originally obtained. The second one considers the diagnosis of pathologies of the vertebral column. The original method achieves accuracies ranging from 76.5% to 96.7%, and from 82.3% to 97.1% in two different cross-validation schemes. Even with no supervision, the proposed method reaches 96.71% and 97.32% in these two cases. By using a supervised framework the achieved accuracy is 97.74%. Furthermore, all abnormal cases were correctly classified.