Results 261 to 270 of about 212,260 (313)

Improved Preoperative Diagnosis of Medullary Thyroid Carcinoma Using Dual-Mode Ultrasound Radiomics. [PDF]

Cancers (Basel)
Gao L, Li N, Xia Y, Ma L, An Y, Ji J, Gu J, Zhang D, Luo N, Cao Y, Fan Y, Jiang Y.   +11 more
europepmc   +1 more source

Privacy-Aware Synthetic Tabular Data Generation for Healthcare: Application to Sepsis Detection. [PDF]

Bioengineering (Basel)
Macias-Fassio E, Morales A, Pruenza C, Fierrez J, Espósito C.   +4 more
europepmc   +1 more source

A Reproducible MRI-Based Quantitative Feature for Differentiating Dysplastic Nodules from Hepatocellular Carcinoma: A Multicenter Retrospective Study. [PDF]

J Hepatocell Carcinoma
Zhang C, Xie S, Wang C, Ren T, Zhong X, Zhang Y, Li S, Wu W, Sun Y, Xie C.   +9 more
europepmc   +1 more source

Discovering non-linear dynamics of miRNAs in Alzheimer's disease-related cognitive impairment: a cross-species approach with explainable machine learning. [PDF]

Biol Direct
Lee SH, Kim S, Lee SB.
europepmc   +1 more source

Laser-induced hyperspectral fluorescence for spatio-chemical detection of sunscreen contaminants in food-grade sea salt using sparse PCA-SVM analysis. [PDF]

Environ Geochem Health
Ebrahem M, Hosni MI, Abdallah A, Mahmoud A.   +3 more
europepmc   +1 more source

Pavement condition prediction under small-sample conditions using a particle swarm optimization-based support vector machine. [PDF]

Sci Prog
Xu W, Yang Z, Ji Y, Huang P.
europepmc   +1 more source

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Railway dangerous goods transportation system risk identification: Comparisons among SVM, PSO-SVM, GA-SVM and GS-SVM

Applied Soft Computing Journal, 2021
Abstract In this paper, three algorithms are applied to obtain the parameters of Radial Basis Function (RBF) kernels of Support Vector Machines (SVM), which include: PSO (Particle Swarm Optimization), GA (Genetic Algorithm) and GS (Grid Search).
Wencheng Huang, Yue Zhang, Bin Shuai
exaly   +2 more sources

Learning using privileged information: SVM+ and weighted SVM [PDF]

Neural Networks, 2014
Prior knowledge can be used to improve predictive performance of learning algorithms or reduce the amount of data required for training. The same goal is pursued within the learning using privileged information paradigm which was recently introduced by Vapnik et al.
Matthias Hein, Bernt Schiele
exaly   +6 more sources

Generalization of Parameter Selection of SVM and LS-SVM for Regression [PDF]

Machine Learning and Knowledge Extraction, 2019
A Support Vector Machine (SVM) for regression is a popular machine learning model that aims to solve nonlinear function approximation problems wherein explicit model equations are difficult to formulate. The performance of an SVM depends largely on the selection of its parameters.
Jiye Zeng, Tsuneo Matsunaga, Tomoko Shirai   +2 more
exaly   +3 more sources

PB-SVM Ensemble: A SVM Ensemble Algorithm Based on SVM

Applied Mechanics and Materials, 2014
As one of the most popular and effective classification algorithms, Support Vector Machine (SVM) has attracted much attention in recent years. Classifiers ensemble is a research direction in machine learning and statistics, it often gives a higher classification accuracy than the single classifier.
Bo Wang, Yu Kai Yao, Xiao Ping Wang, Xiao Yun Chen   +3 more
openaire   +1 more source