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» Two Methods for Validating Brain Tissue Classifiers
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AIME
1997
Springer
13 years 11 months ago
Detecting Very Early Stages of Dementia from Normal Aging with Machine Learning Methods
We used Machine Learning (ML) methods to learn the best decision rules to distinguish normal brain aging from the earliest stages of dementia using subsamples of 198 normal and 244...
William Rodman Shankle, Subramani Mani, Michael J....
TMI
2010
206views more  TMI 2010»
13 years 2 months ago
Random Subspace Ensembles for fMRI Classification
Classification of brain images obtained through functional magnetic resonance imaging (fMRI) poses a serious challenge to pattern recognition and machine learning due to the extrem...
Ludmila I. Kuncheva, Juan José Rodrí...
BMCBI
2006
110views more  BMCBI 2006»
13 years 7 months ago
Bias in error estimation when using cross-validation for model selection
Background: Cross-validation (CV) is an effective method for estimating the prediction error of a classifier. Some recent articles have proposed methods for optimizing classifiers...
Sudhir Varma, Richard Simon
IPMI
2005
Springer
14 years 8 months ago
Regional Whole Body Fat Quantification in Mice
Obesity has risen to epidemic levels in the United States and around the world. Global indices of obesity such as the body mass index (BMI) have been known to be inaccurate predict...
Xenophon Papademetris, Pavel Shkarin, Lawrence H. ...
BMCBI
2005
103views more  BMCBI 2005»
13 years 7 months ago
Many accurate small-discriminatory feature subsets exist in microarray transcript data: biomarker discovery
Background: Molecular profiling generates abundance measurements for thousands of gene transcripts in biological samples such as normal and tumor tissues (data points). Given such...
Leslie Grate