COMPARE: classification of morphological patterns using adaptive regional elements
This paper presents a method for classification of structural brain magnetic resonance (MR)
images, by using a combination of deformation-based morphometry and machine learning …
images, by using a combination of deformation-based morphometry and machine learning …
High-dimensional pattern regression using machine learning: from medical images to continuous clinical variables
This paper presents a general methodology for high-dimensional pattern regression on
medical images via machine learning techniques. Compared with pattern classification …
medical images via machine learning techniques. Compared with pattern classification …
Generative embedding for model-based classification of fMRI data
KH Brodersen, TM Schofield, AP Leff… - PLoS computational …, 2011 - journals.plos.org
Decoding models, such as those underlying multivariate classification algorithms, have
been increasingly used to infer cognitive or clinical brain states from measures of brain …
been increasingly used to infer cognitive or clinical brain states from measures of brain …
Multivariate examination of brain abnormality using both structural and functional MRI
A multivariate classification approach has been presented to examine the brain
abnormalities, ie, due to prenatal cocaine exposure, using both structural and functional …
abnormalities, ie, due to prenatal cocaine exposure, using both structural and functional …
Preprocessing, classification modeling and feature selection using flow injection electrospray mass spectrometry metabolite fingerprint data
Metabolome analysis by flow injection electrospray mass spectrometry (FIE-MS)
fingerprinting generates measurements relating to large numbers of m/z signals. Such data …
fingerprinting generates measurements relating to large numbers of m/z signals. Such data …
Websites' data: a new asset for enhancing credit risk modeling
Recent literature shows an increasing interest in considering alternative sources of
information for predicting Small and Medium Enterprises default. The usage of accounting …
information for predicting Small and Medium Enterprises default. The usage of accounting …
Generative-discriminative basis learning for medical imaging
NK Batmanghelich, B Taskar… - IEEE transactions on …, 2011 - ieeexplore.ieee.org
This paper presents a novel dimensionality reduction method for classification in medical
imaging. The goal is to transform very high-dimensional input (typically, millions of voxels) to …
imaging. The goal is to transform very high-dimensional input (typically, millions of voxels) to …
Personal values and credit scoring: new insights in the financial prediction
C Liberati, F Camillo - Journal of the Operational Research Society, 2018 - Taylor & Francis
The objective of quantitative credit scoring is to develop accurate models of classification.
Most attention has been devoted to deliver new classifiers based on variables commonly …
Most attention has been devoted to deliver new classifiers based on variables commonly …
Investigating brain structural patterns in first episode psychosis and schizophrenia using MRI and a machine learning approach
AM de Moura, WHL Pinaya, A Gadelha… - Psychiatry Research …, 2018 - Elsevier
In this study, we employed the Maximum Uncertainty Linear Discriminant Analysis (MLDA) to
investigate whether the structural brain patterns in first episode psychosis (FEP) patients …
investigate whether the structural brain patterns in first episode psychosis (FEP) patients …
Predicting the shapes of bones at a joint: application to the shoulder
YM Yang, D Rueckert, AMJ Bull - Computer Methods in …, 2008 - Taylor & Francis
This paper presents a novel method to explore the intrinsic morphological correlation
between the bones of a shoulder joint (humerus and scapula). To model this correlation …
between the bones of a shoulder joint (humerus and scapula). To model this correlation …