AIMC Topic: Algorithms

Clear Filters Showing 21401 to 21410 of 28713 articles

Auditing SNOMED CT hierarchical relations based on lexical features of concepts in non-lattice subgraphs.

Journal of biomedical informatics
OBJECTIVE: We introduce a structural-lexical approach for auditing SNOMED CT using a combination of non-lattice subgraphs of the underlying hierarchical relations and enriched lexical attributes of fully specified concept names. Our goal is to develo...

Enhancing Evolutionary Couplings with Deep Convolutional Neural Networks.

Cell systems
While genes are defined by sequence, in biological systems a protein's function is largely determined by its three-dimensional structure. Evolutionary information embedded within multiple sequence alignments provides a rich source of data for inferri...

White matter hyperintensity and stroke lesion segmentation and differentiation using convolutional neural networks.

NeuroImage. Clinical
White matter hyperintensities (WMH) are a feature of sporadic small vessel disease also frequently observed in magnetic resonance images (MRI) of healthy elderly subjects. The accurate assessment of WMH burden is of crucial importance for epidemiolog...

Accurate and fast feature selection workflow for high-dimensional omics data.

PloS one
We are moving into the age of 'Big Data' in biomedical research and bioinformatics. This trend could be encapsulated in this simple formula: D = S * F, where the volume of data generated (D) increases in both dimensions: the number of samples (S) and...

Vector similarity measures of hesitant fuzzy linguistic term sets and their applications.

PloS one
In decision making, similarity measure and distance between two objects are crucial to be able to determine the relationship between those objects. Many researchers have received much attention for their research on this subject. In this study, we pr...

An improved wrapper-based feature selection method for machinery fault diagnosis.

PloS one
A major issue of machinery fault diagnosis using vibration signals is that it is over-reliant on personnel knowledge and experience in interpreting the signal. Thus, machine learning has been adapted for machinery fault diagnosis. The quantity and qu...

Epileptic Seizures Prediction Using Machine Learning Methods.

Computational and mathematical methods in medicine
Epileptic seizures occur due to disorder in brain functionality which can affect patient's health. Prediction of epileptic seizures before the beginning of the onset is quite useful for preventing the seizure by medication. Machine learning technique...

Sparsifying machine learning models identify stable subsets of predictive features for behavioral detection of autism.

Molecular autism
BACKGROUND: Autism spectrum disorder (ASD) diagnosis can be delayed due in part to the time required for administration of standard exams, such as the Autism Diagnostic Observation Schedule (ADOS). Shorter and potentially mobilized approaches would h...

Classification of optic disc shape in glaucoma using machine learning based on quantified ocular parameters.

PloS one
PURPOSE: This study aimed to develop a machine learning-based algorithm for objective classification of the optic disc in patients with open-angle glaucoma (OAG), using quantitative parameters obtained from ophthalmic examination instruments.