AIMC Topic: Support Vector Machine

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SVM-Enabled Intelligent Genetic Algorithmic Model for Realizing Efficient Universal Feature Selection in Breast Cyst Image Acquired via Ultrasound Sensing Systems.

Sensors (Basel, Switzerland)
In recent years, there are several cost-effective intelligent sensing systems such as ultrasound imaging systems for visualizing the internal body structures of the body. Further, such intelligent sensing systems such as ultrasound systems have been ...

Object parsing in the left lateral occipitotemporal cortex: Whole shape, part shape, and graspability.

Neuropsychologia
Small and manipulable objects (tools) preferentially evoke a network of brain regions relative to other objects, including the lateral occipitotemporal cortex (LOTC), which is assumed to process tool shape information. Given the correlation between v...

Polygenic risk scores outperform machine learning methods in predicting coronary artery disease status.

Genetic epidemiology
Coronary artery disease (CAD) is the leading global cause of mortality and has substantial heritability with a polygenic architecture. Recent approaches of risk prediction were based on polygenic risk scores (PRS) not taking possible nonlinear effect...

An effective approach for CT lung segmentation using mask region-based convolutional neural networks.

Artificial intelligence in medicine
Computer vision systems have numerous tools to assist in various medical fields, notably in image diagnosis. Computed tomography (CT) is the principal imaging method used to assist in the diagnosis of diseases such as bone fractures, lung cancer, hea...

Constructing a Consciousness Meter Based on the Combination of Non-Linear Measurements and Genetic Algorithm-Based Support Vector Machine.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
OBJECTIVE: Constructing a framework to evaluate consciousness is an important issue in neuroscience research and clinical practice. However, there is still no systematic framework for quantifying altered consciousness along the dimensions of both lev...

Fatigue Evaluation through Machine Learning and a Global Fatigue Descriptor.

Journal of healthcare engineering
Research in physiology and sports science has shown that fatigue, a complex psychophysiological phenomenon, has a relevant impact in performance and in the correct functioning of our motricity system, potentially being a cause of damage to the human ...

Interpreting neural decoding models using grouped model reliance.

PLoS computational biology
Machine learning algorithms are becoming increasingly popular for decoding psychological constructs based on neural data. However, as a step towards bridging the gap between theory-driven cognitive neuroscience and data-driven decoding approaches, th...

Medical data set classification using a new feature selection algorithm combined with twin-bounded support vector machine.

Medical & biological engineering & computing
Early diagnosis and treatment are the most important strategies to prevent deaths from several diseases. In this regard, data mining and machine learning techniques have been useful tools to help minimize errors and to provide useful information for ...

A Multidimensional Neural Maturation Index Reveals Reproducible Developmental Patterns in Children and Adolescents.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Adolescence is a time of extensive neural restructuring, leaving one susceptible to atypical development. Although neural maturation in humans can be measured using functional and structural MRI, the subtle patterns associated with the initial stages...