AIMC Topic: Models, Statistical

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Improving the Mann-Whitney statistical test for feature selection: an approach in breast cancer diagnosis on mammography.

Artificial intelligence in medicine
OBJECTIVE: This work addresses the theoretical description and experimental evaluation of a new feature selection method (named uFilter). The uFilter improves the Mann-Whitney U-test for reducing dimensionality and ranking features in binary classifi...

Colored Traveling Salesman Problem.

IEEE transactions on cybernetics
The multiple traveling salesman problem (MTSP) is an important combinatorial optimization problem. It has been widely and successfully applied to the practical cases in which multiple traveling individuals (salesmen) share the common workspace (city ...

Sparse representation of electrodermal activity with knowledge-driven dictionaries.

IEEE transactions on bio-medical engineering
Biometric sensors and portable devices are being increasingly embedded into our everyday life, creating the need for robust physiological models that efficiently represent, analyze, and interpret the acquired signals. We propose a knowledge-driven me...

Learning structured models for segmentation of 2-D and 3-D imagery.

IEEE transactions on medical imaging
Efficient and accurate segmentation of cellular structures in microscopic data is an essential task in medical imaging. Many state-of-the-art approaches to image segmentation use structured models whose parameters must be carefully chosen for optimal...

Clinical time series prediction: Toward a hierarchical dynamical system framework.

Artificial intelligence in medicine
OBJECTIVE: Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventi...

An Evolutionary Algorithm with Double-Level Archives for Multiobjective Optimization.

IEEE transactions on cybernetics
Existing multiobjective evolutionary algorithms (MOEAs) tackle a multiobjective problem either as a whole or as several decomposed single-objective sub-problems. Though the problem decomposition approach generally converges faster through optimizing ...

Ensemble learning of inverse probability weights for marginal structural modeling in large observational datasets.

Statistics in medicine
Inverse probability weights used to fit marginal structural models are typically estimated using logistic regression. However, a data-adaptive procedure may be able to better exploit information available in measured covariates. By combining predicti...

Predictive Models Based on Support Vector Machines: Whole-Brain versus Regional Analysis of Structural MRI in the Alzheimer's Disease.

Journal of neuroimaging : official journal of the American Society of Neuroimaging
Decision-making systems trained on structural magnetic resonance imaging data of subjects affected by the Alzheimer's disease (AD) and healthy controls (CTRL) are becoming widespread prognostic tools for subjects with mild cognitive impairment (MCI)....

Adaptive Neural Control of Nonaffine Systems With Unknown Control Coefficient and Nonsmooth Actuator Nonlinearities.

IEEE transactions on neural networks and learning systems
This brief considers the asymptotic tracking problem for a class of high-order nonaffine nonlinear dynamical systems with nonsmooth actuator nonlinearities. A novel transformation approach is proposed, which is able to systematically transfer the ori...

A multi-technique approach to bridge electronic case report form design and data standard adoption.

Journal of biomedical informatics
BACKGROUND AND OBJECTIVE: The importance of data standards when integrating clinical research data has been recognized. The common data element (CDE) is a consensus-based data element for data harmonization and sharing between clinical researchers, i...