AIMC Topic: Support Vector Machine

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Evaluation of classification and forecasting methods on time series gene expression data.

PloS one Nov 6, 2020
Time series gene expression data is widely used to study different dynamic biological processes. Although gene expression datasets share many of the characteristics of time series data from other domains, most of the analyses in this field do not ful...
Humans Neural Networks, Computer Forecasting Deep Learning Support Vector Machine Supervised Machine Learning
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Improving area of occupancy estimates for parapatric species using distribution models and support vector machines.

Ecological applications : a publication of the Ecological Society of America Nov 4, 2020
As geographic range estimates for the IUCN Red List guide conservation actions, accuracy and ecological realism are crucial. IUCN's extent of occurrence (EOO) is the general region including the species' range, while area of occupancy (AOO) is the su...
Support Vector Machine Climate Change Climate Animals Ecosystem Mice
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Concentration-Emission Matrix (CEM) Spectroscopy Combined with GA-SVM: An Analytical Method to Recognize Oil Species in Marine.

Molecules (Basel, Switzerland) Nov 4, 2020
The establishment and development of a set of methods of oil accurate recognition in a different environment are of great significance to the effective management of oil spill pollution. In this work, the concentration-emission matrix (CEM) is formed...
Petroleum Petroleum Pollution Water Pollutants, Chemical Principal Component Analysis Seawater Spectroscopy, Near-Infrared Support Vector Machine
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Can pre-trained convolutional neural networks be directly used as a feature extractor for video-based neonatal sleep and wake classification?

BMC research notes Nov 4, 2020
OBJECTIVE: In this paper, we propose to evaluate the use of pre-trained convolutional neural networks (CNNs) as a features extractor followed by the Principal Component Analysis (PCA) to find the best discriminant features to perform classification u...
Sleep Video Recording Infant, Newborn Support Vector Machine Humans Neural Networks, Computer Algorithms
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A Model Using Support Vector Machines Recursive Feature Elimination (SVM-RFE) Algorithm to Classify Whether COPD Patients Have Been Continuously Managed According to GOLD Guidelines.

International journal of chronic obstructive pulmonary disease Nov 4, 2020
PURPOSE: Patients with chronic obstructive pulmonary disease (COPD) would have a poor prognosis if they were not continuously managed according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) guidelines. We aim to develop a model...
Support Vector Machine Prospective Studies Retrospective Studies Humans Pulmonary Disease, Chronic Obstructive Algorithms
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Predictive diagnosis of chronic obstructive pulmonary disease using serum metabolic biomarkers and least-squares support vector machine.

Journal of clinical laboratory analysis Nov 3, 2020
OBJECTIVE: Development of biofluid-based biomarkers is attractive for the diagnosis of chronic obstructive pulmonary disease (COPD) but still lacking. Thus, here we aimed to identify serum metabolic biomarkers for the diagnosis of COPD.
Humans Aged Pulmonary Disease, Chronic Obstructive Male Artificial Intelligence Biomarkers Female Least-Squares Analysis Magnetic Resonance Spectroscopy Diagnosis, Computer-Assisted Support Vector Machine Metabolomics Middle Aged Case-Control Studies
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A bilinear convolutional neural network for lung nodules classification on CT images.

International journal of computer assisted radiology and surgery Nov 2, 2020
PURPOSE: Lung cancer is the most frequent cancer worldwide and is the leading cause of cancer-related deaths. Its early detection and treatment at the stage of a lung nodule improve the prognosis. In this study was proposed a new classification appro...
Lung Neoplasms Humans Neural Networks, Computer Support Vector Machine Tomography, X-Ray Computed Lung Solitary Pulmonary Nodule Diagnosis, Computer-Assisted
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A novel extended Kalman filter with support vector machine based method for the automatic diagnosis and segmentation of brain tumors.

Computer methods and programs in biomedicine Oct 31, 2020
BACKGROUND: Brain tumors are life-threatening, and their early detection is crucial for improving survival rates. Conventionally, brain tumors are detected by radiologists based on their clinical experience. However, this process is inefficient. This...
Humans Neural Networks, Computer Algorithms Magnetic Resonance Imaging Brain Neoplasms Image Processing, Computer-Assisted Support Vector Machine
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m5CPred-SVM: a novel method for predicting m5C sites of RNA.

BMC bioinformatics Oct 30, 2020
BACKGROUND: As one of the most common post-transcriptional modifications (PTCM) in RNA, 5-cytosine-methylation plays important roles in many biological functions such as RNA metabolism and cell fate decision. Through accurate identification of 5-meth...
Base Sequence Arabidopsis 5-Methylcytosine Humans Support Vector Machine Internet Animals RNA ROC Curve Mice
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Scalable classification of organisms into a taxonomy using hierarchical supervised learners.

Journal of bioinformatics and computational biology Oct 29, 2020
Accurately identifying organisms based on their partially available genetic material is an important task to explore the phylogenetic diversity in an environment. Specific fragments in the DNA sequence of a living organism have been defined as DNA ba...
Algorithms Animals Fungi DNA Barcoding, Taxonomic Classification Deep Learning Chiroptera Birds Support Vector Machine Rodentia Phylogeny Databases, Genetic Ferns
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