AIMC Topic: Support Vector Machine

Clear Filters Showing 2691 to 2700 of 4975 articles

Radiomics features on non-contrast computed tomography predict early enlargement of spontaneous intracerebral hemorrhage.

Clinical neurology and neurosurgery
OBJECTIVE: To explore the value of radiomics features on non-contrast computed tomography (NCCT) in predicting early enlargement of spontaneous intracerebral hemorrhage (SICH).

A parallel method for accelerating visualization and interactivity for vector tiles.

PloS one
Vector tile technology is developing rapidly and has received increasing attention in recent years. Compared to the raster tile, the vector tile has shown incomparable advantages, such as flexible map styles, suitability for high-resolution screens a...

Assisted therapeutic system based on reinforcement learning for children with autism.

Computer assisted surgery (Abingdon, England)
Assisted therapy is increasingly used in autism spectrum disorders (ASD) for improving social interaction and communication skills in recent years. A lot of studies have proven that the form of interactive games for therapy has a good effect on child...

Clustering-based undersampling with random over sampling examples and support vector machine for imbalanced classification of breast cancer diagnosis.

Computer assisted surgery (Abingdon, England)
To overcome the two-class imbalanced classification problem existing in the diagnosis of breast cancer, a hybrid of Random Over Sampling Example, K-means and Support vector machine (RK-SVM) model is proposed which is based on sample selection. Random...

Flexible model of network embedding.

Scientific reports
There has lately been increased interest in describing complex systems not merely as single networks but rather as collections of networks that are coupled to one another. We introduce an analytically tractable model that enables one to connect two l...

SecProMTB: Support Vector Machine-Based Classifier for Secretory Proteins Using Imbalanced Data Sets Applied to Mycobacterium tuberculosis.

Proteomics
Secretory proteins of Mycobacterium tuberculosis have created more concern, given their dominant immunogenicity and role in pathogenesis. In view of expensive and time-consuming traditional biochemical experiments, an advanced support vector machine ...

MLMDA: a machine learning approach to predict and validate MicroRNA-disease associations by integrating of heterogenous information sources.

Journal of translational medicine
BACKGROUND: Emerging evidences show that microRNA (miRNA) plays an important role in many human complex diseases. However, considering the inherent time-consuming and expensive of traditional in vitro experiments, more and more attention has been pai...

Classification of schizophrenia and normal controls using 3D convolutional neural network and outcome visualization.

Schizophrenia research
BACKGROUND: The recent deep learning-based studies on the classification of schizophrenia (SCZ) using MRI data rely on manual extraction of feature vector, which destroys the 3D structure of MRI data. In order to both identify SCZ and find relevant b...

Novel deep learning model for more accurate prediction of drug-drug interaction effects.

BMC bioinformatics
BACKGROUND: Predicting the effect of drug-drug interactions (DDIs) precisely is important for safer and more effective drug co-prescription. Many computational approaches to predict the effect of DDIs have been proposed, with the aim of reducing the ...

Automatic cataract grading methods based on deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The shortage of ophthalmologists in rural areas in China causes a lot of cataract patients not getting timely diagnosis and effective treatment. We develop an algorithm and platform to automatically diagnose and grade catara...