AIMC Topic: Algorithms

Clear Filters Showing 23141 to 23150 of 28713 articles

A Robust e-Epidemiology Tool in Phenotyping Heart Failure with Differentiation for Preserved and Reduced Ejection Fraction: the Electronic Medical Records and Genomics (eMERGE) Network.

Journal of cardiovascular translational research
Identifying populations of heart failure (HF) patients is paramount to research efforts aimed at developing strategies to effectively reduce the burden of this disease. The use of electronic medical record (EMR) data for this purpose is challenging g...

SFM: A novel sequence-based fusion method for disease genes identification and prioritization.

Journal of theoretical biology
The identification of disease genes from human genome is of great importance to improve diagnosis and treatment of disease. Several machine learning methods have been introduced to identify disease genes. However, these methods mostly differ in the p...

A Bayesian approach to distinguishing interdigitated tongue muscles from limited diffusion magnetic resonance imaging.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The tongue is a critical organ for a variety of functions, including swallowing, respiration, and speech. It contains intrinsic and extrinsic muscles that play an important role in changing its shape and position. Diffusion tensor imaging (DTI) has b...

Matrix measure method for global exponential stability of complex-valued recurrent neural networks with time-varying delays.

Neural networks : the official journal of the International Neural Network Society
In this paper, based on the matrix measure method and the Halanay inequality, global exponential stability problem is investigated for the complex-valued recurrent neural networks with time-varying delays. Without constructing any Lyapunov functions,...

Relevance Vector Machines: Sparse Classification Methods for QSAR.

Journal of chemical information and modeling
Sparse machine learning methods have provided substantial benefits to quantitative structure property modeling, as they make model interpretation simpler and generate models with improved predictivity. Sparsity is usually induced via Bayesian regular...

Sample Selection for Training Cascade Detectors.

PloS one
Automatic detection systems usually require large and representative training datasets in order to obtain good detection and false positive rates. Training datasets are such that the positive set has few samples and/or the negative set should represe...

Use of Semisupervised Clustering and Feature-Selection Techniques for Identification of Co-expressed Genes.

IEEE journal of biomedical and health informatics
Studying the patterns hidden in gene-expression data helps to understand the functionality of genes. In general, clustering techniques are widely used for the identification of natural partitionings from the gene expression data. In order to put cons...

Exploring multifractal-based features for mild Alzheimer's disease classification.

Magnetic resonance in medicine
PURPOSE: Multifractal applications to resting state functional MRI (rs-fMRI) time series for diagnosing Alzheimer's disease (AD) are still limited. We aim to address two issues: (I) if and what multifractal features are sufficiently discriminative to...

Feature-based fuzzy connectedness segmentation of ultrasound images with an object completion step.

Medical image analysis
Medical ultrasound (US) image segmentation and quantification can be challenging due to signal dropouts, missing boundaries, and presence of speckle, which gives images of similar objects quite different appearance. Typically, purely intensity-based ...