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TMI
2008
138views more  TMI 2008»
13 years 7 months ago
Dynamic Positron Emission Tomography Data-Driven Analysis Using Sparse Bayesian Learning
A method is presented for the analysis of dynamic positron emission tomography (PET) data using sparse Bayesian learning. Parameters are estimated in a compartmental framework usin...
Jyh-Ying Peng, John A. D. Aston, R. N. Gunn, Cheng...
ML
2000
ACM
157views Machine Learning» more  ML 2000»
13 years 7 months ago
A Multistrategy Approach to Classifier Learning from Time Series
We present an approach to inductive concept learning using multiple models for time series. Our objective is to improve the efficiency and accuracy of concept learning by decomposi...
William H. Hsu, Sylvian R. Ray, David C. Wilkins
ICIP
2006
IEEE
14 years 9 months ago
Curvelet-Based Texture Classification of Tissues in Computed Tomography
The research presented in this article is aimed at the development of an automated imaging system for classification of tissues in medical images obtained from Computed Tomography...
Lindsay Semler, Lucia Dettori
KDD
2012
ACM
238views Data Mining» more  KDD 2012»
11 years 10 months ago
Multi-source learning for joint analysis of incomplete multi-modality neuroimaging data
Incomplete data present serious problems when integrating largescale brain imaging data sets from different imaging modalities. In the Alzheimer’s Disease Neuroimaging Initiativ...
Lei Yuan, Yalin Wang, Paul M. Thompson, Vaibhav A....
JMLR
2008
104views more  JMLR 2008»
13 years 7 months ago
Learning Reliable Classifiers From Small or Incomplete Data Sets: The Naive Credal Classifier 2
In this paper, the naive credal classifier, which is a set-valued counterpart of naive Bayes, is extended to a general and flexible treatment of incomplete data, yielding a new cl...
Giorgio Corani, Marco Zaffalon