AIMC Topic: Support Vector Machine

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SNRFCB: sub-network based random forest classifier for predicting chemotherapy benefit on survival for cancer treatment.

Molecular bioSystems
Adjuvant chemotherapy (CTX) should be individualized to provide potential survival benefit and avoid potential harm to cancer patients. Our goal was to establish a computational approach for making personalized estimates of the survival benefit from ...

Effect of Subliminal Lexical Priming on the Subjective Perception of Images: A Machine Learning Approach.

PloS one
The purpose of the study is to examine the effect of subliminal priming in terms of the perception of images influenced by words with positive, negative, and neutral emotional content, through electroencephalograms (EEGs). Participants were instructe...

Data mining framework for identification of myocardial infarction stages in ultrasound: A hybrid feature extraction paradigm (PART 2).

Computers in biology and medicine
Early expansion of infarcted zone after Acute Myocardial Infarction (AMI) has serious short and long-term consequences and contributes to increased mortality. Thus, identification of moderate and severe phases of AMI before leading to other catastrop...

Multivoxel Object Representations in Adult Human Visual Cortex Are Flexible: An Associative Learning Study.

Journal of cognitive neuroscience
Learning associations between co-occurring events enables us to extract structure from our environment. Medial-temporal lobe structures are critical for associative learning. However, the role of the ventral visual pathway (VVP) in associative learni...

Sequence-based prediction of protein-peptide binding sites using support vector machine.

Journal of computational chemistry
Protein-peptide interactions are essential for all cellular processes including DNA repair, replication, gene-expression, and metabolism. As most protein-peptide interactions are uncharacterized, it is cost effective to investigate them computational...

Multivariate pattern classification of pediatric Tourette syndrome using functional connectivity MRI.

Developmental science
Tourette syndrome (TS) is a developmental neuropsychiatric disorder characterized by motor and vocal tics. Individuals with TS would benefit greatly from advances in prediction of symptom timecourse and treatment effectiveness. As a first step, we ap...

Drug-Drug Interaction Extraction via Convolutional Neural Networks.

Computational and mathematical methods in medicine
Drug-drug interaction (DDI) extraction as a typical relation extraction task in natural language processing (NLP) has always attracted great attention. Most state-of-the-art DDI extraction systems are based on support vector machines (SVM) with a lar...

An ensemble of dynamic neural network identifiers for fault detection and isolation of gas turbine engines.

Neural networks : the official journal of the International Neural Network Society
In this paper, a new approach for Fault Detection and Isolation (FDI) of gas turbine engines is proposed by developing an ensemble of dynamic neural network identifiers. For health monitoring of the gas turbine engine, its dynamics is first identifie...

Combination of the Manifold Dimensionality Reduction Methods with Least Squares Support vector machines for Classifying the Species of Sorghum Seeds.

Scientific reports
This study was carried out for rapid and noninvasive determination of the class of sorghum species by using the manifold dimensionality reduction (MDR) method and the nonlinear regression method of least squares support vector machines (LS-SVM) combi...

ChemTok: A New Rule Based Tokenizer for Chemical Named Entity Recognition.

BioMed research international
Named Entity Recognition (NER) from text constitutes the first step in many text mining applications. The most important preliminary step for NER systems using machine learning approaches is tokenization where raw text is segmented into tokens. This ...