AIMC Topic: Support Vector Machine

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Hybrid adversarial-discriminative network for leukocyte classification in leukemia.

Medical physics
PURPOSE: Leukemia is a lethal disease that is harmful to bone marrow and overall blood health. The classification of white blood cell images is crucial for leukemia diagnosis. The purpose of this study is to classify white blood cells by extracting d...

A machine learning-based framework for Predicting Treatment Failure in tuberculosis: A case study of six countries.

Tuberculosis (Edinburgh, Scotland)
Tuberculosis is ranked as the 2nd deadliest disease in the world and is responsible for ten million deaths in 2017. Treatment failure is one of a main reason behind these deaths. Reasons of treatment failure are still unknown and the death rate due t...

Enhancer recognition and prediction during spermatogenesis based on deep convolutional neural networks.

Molecular omics
MOTIVATION: enhancers play an important role in the regulation of gene expression during spermatogenesis. The development of ChIP-Chip and ChIP-Seq sequencing technology has enabled researchers to focus on the relationship between enhancers and DNA s...

Hybrid SVM-CNN Classification Technique for Human-Vehicle Targets in an Automotive LFMCW Radar.

Sensors (Basel, Switzerland)
Human-vehicle classification is an essential component to avoiding accidents in autonomous driving. The classification technique based on the automotive radar sensor has been paid more attention by related researchers, owing to its robustness to low-...

Automated traffic incident detection with a smaller dataset based on generative adversarial networks.

Accident; analysis and prevention
An imbalanced and small training sample can cause an incident detection model to have a low detection rate and a high false alarm rate. To solve the scarcity of incident samples, a novel incident detection framework is proposed based on generative ad...

Meta-iPVP: a sequence-based meta-predictor for improving the prediction of phage virion proteins using effective feature representation.

Journal of computer-aided molecular design
Phage virion protein (PVP) perforate the host cell membrane and eventually culminates in cell rupture thereby releasing replicated phages. The accurate identification of PVP is thus a crucial step towards improving our understanding of the biological...

Decoding attention control and selection in visual spatial attention.

Human brain mapping
Event-related potentials (ERPs) are used extensively to investigate the neural mechanisms of attention control and selection. The univariate ERP approach, however, has left important questions inadequately answered. We addressed two questions by appl...

A Support Vector Machine Model Predicting the Risk of Duodenal Cancer in Patients with Familial Adenomatous Polyposis at the Transcript Levels.

BioMed research international
OBJECTIVE: Familial adenomatous polyposis (FAP) is one major type of inherited duodenal cancer. The estimate of duodenal cancer risk in patients with FAP is critical for selecting the optimal treatment strategy.

Optimized Attribute Selection Using Artificial Plant (AP) Algorithm with ESVM Classifier (AP-ESVM) and Improved Singular Value Decomposition (ISVD)-Based Dimensionality Reduction for Large Micro-array Biological Data.

Interdisciplinary sciences, computational life sciences
In the tremendous field of the bioinformatics look into, enormous volume of genetic information has been produced. Higher throughput gadgets are made accessible at lower cost made the age of Big data. In a time of developing information multifaceted ...