Predictive markers for AD in a multi-modality framework: an analysis of MCI progression in the ADNI population
Alzheimer's Disease (AD) and other neurodegenerative diseases affect over 20 million
people worldwide, and this number is projected to significantly increase in the coming …
people worldwide, and this number is projected to significantly increase in the coming …
Uncertainty-based active learning by bayesian U-Net for Multi-Label Cone-Beam CT segmentation
J Huang, N Farpour, BJ Yang, M Mupparapu… - Journal of …, 2024 - Elsevier
Abstract Introduction Training of Artificial Intelligence (AI) for biomedical image analysis
depends on large annotated datasets. This study assessed the efficacy of Active Learning …
depends on large annotated datasets. This study assessed the efficacy of Active Learning …
Q-mkl: Matrix-induced regularization in multi-kernel learning with applications to neuroimaging
Abstract Multiple Kernel Learning (MKL) generalizes SVMs to the setting where one
simultaneously trains a linear classifier and chooses an optimal combination of given base …
simultaneously trains a linear classifier and chooses an optimal combination of given base …
Impact of visual features on the segmentation of gastroenterology images using normalized cuts
F Riaz, FB Silva, MD Ribeiro… - IEEE Transactions on …, 2012 - ieeexplore.ieee.org
Gastroenterology imaging is an essential tool to detect gastrointestinal cancer in patients.
Computer-assisted diagnosis is desirable to help us improve the reliability of this detection …
Computer-assisted diagnosis is desirable to help us improve the reliability of this detection …
Sparse solutions to random standard quadratic optimization problems
The standard quadratic optimization problem (StQP) refers to the problem of minimizing a
quadratic form over the standard simplex. Such a problem arises from numerous …
quadratic form over the standard simplex. Such a problem arises from numerous …
New analysis on sparse solutions to random standard quadratic optimization problems and extensions
The standard quadratic optimization problem (StQP) refers to the problem of minimizing a
quadratic form over the standard simplex. Such a problem arises from numerous …
quadratic form over the standard simplex. Such a problem arises from numerous …
[PDF][PDF] Learning-Based Methods for Outlier Detection in Imbalanced and Heterogeneous Data
S Dang - 2018 - unsworks.unsw.edu.au
This thesis describes novel approaches to the problem of outlier detection. It is one of the
most important problems in the field of machine learning and widely used in various …
most important problems in the field of machine learning and widely used in various …
On sparsity of the solution to a random quadratic optimization problem
X Chen, B Pittel - Mathematical Programming, 2021 - Springer
The standard quadratic optimization problem (StQP), ie the problem of minimizing a
quadratic form x^ TQ xx TQ x on the standard simplex {x ≥ 0: x^ T e= 1\} x≥ 0: x T e= 1, is …
quadratic form x^ TQ xx TQ x on the standard simplex {x ≥ 0: x^ T e= 1\} x≥ 0: x T e= 1, is …
Multi-Modality Inference Methods for Neuroimaging with Applications to Alzheimer's Disease Research
CD Hinrichs - 2012 - search.proquest.com
An emphasis in ongoing Alzheimer's disease (AD) research is identifying those biomarkers
which best predict future cognitive decline at the various stages of disease progression …
which best predict future cognitive decline at the various stages of disease progression …
Adaptive cuts for extracting specific white matter tracts
Extracting specific white matter tracts (eg, uncinate fasciculus) from whole brain tractography
has numerous applications in studying individual differences in white matter. Typically …
has numerous applications in studying individual differences in white matter. Typically …