AIMC Topic: Support Vector Machine

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A spectrogram image based intelligent technique for automatic detection of autism spectrum disorder from EEG.

PloS one
Autism spectrum disorder (ASD) is a developmental disability characterized by persistent impairments in social interaction, speech and nonverbal communication, and restricted or repetitive behaviors. Currently Electroencephalography (EEG) is the most...

Predictive modelling of piezometric head and seepage discharge in earth dam using soft computational models.

Environmental science and pollution research international
Predictions of pore pressure and seepage discharge are the most important parameters in the design of earth dams and assessing their safety during the operational period as well. In this research, soft computing models namely multi-layer perceptron n...

Machine-learning models for activity class prediction: A comparative study of feature selection and classification algorithms.

Gait & posture
PURPOSE: Machine-learning (ML) approaches have been repeatedly coupled with raw accelerometry to classify physical activity classes, but the features required to optimize their predictive performance are still unknown. Our aim was to identify appropr...

Universum based Lagrangian twin bounded support vector machine to classify EEG signals.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The detection of brain-related problems and neurological disorders like epilepsy, sleep disorder, and so on is done by using electroencephalogram (EEG) signals which contain noisy signals and outliers. Universum data contain...

Analysis of cognitive impairment in schizophrenia based on machine learning: Interaction between psychological stress and immune system.

Neuroscience letters
The interaction between psychological stress and immune system may be associated with the cognitive impairment of schizophrenia. To employ machine learning algorithms to examine patterns of stress-immune networks with cognitive impairment in chronic ...

Design of an SVM Classifier Assisted Intelligent Receiver for Reliable Optical Camera Communication.

Sensors (Basel, Switzerland)
Embedding optical camera communication (OCC) commercially as a favorable complement of radio-frequency technology has led to the desire for an intelligent receiver system that is eligible to communicate with an accurate light-emitting diode (LED) tra...

Predicting antifreeze proteins with weighted generalized dipeptide composition and multi-regression feature selection ensemble.

BMC bioinformatics
BACKGROUND: Antifreeze proteins (AFPs) are a group of proteins that inhibit body fluids from growing to ice crystals and thus improve biological antifreeze ability. It is vital to the survival of living organisms in extremely cold environments. Howev...

Muscle network topology analysis for the classification of chronic neck pain based on EMG biomarkers extracted during walking.

PloS one
Neuromuscular impairments are frequently observed in patients with chronic neck pain (CNP). This study uniquely investigates whether changes in neck muscle synergies detected during gait are sensitive enough to differentiate between people with and w...

A Nomogram Based on a Collagen Feature Support Vector Machine for Predicting the Treatment Response to Neoadjuvant Chemoradiotherapy in Rectal Cancer Patients.

Annals of surgical oncology
BACKGROUND: The relationship between collagen features (CFs) in the tumor microenvironment and the treatment response to neoadjuvant chemoradiotherapy (nCRT) is still unknown. This study aimed to develop and validate a perdition model based on the CF...

Machine Learning Strategy for Soil Nutrients Prediction Using Spectroscopic Method.

Sensors (Basel, Switzerland)
The research presented in this paper is based on the hypothesis that the machine learning approach improves the accuracy of soil properties prediction. The correlations obtained in this research are important for understanding the overall strategy fo...