AIMC Topic: Pattern Recognition, Automated

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Features extraction and multi-classification of sEMG using a GPU-Accelerated GA/MLP hybrid algorithm.

Journal of X-ray science and technology
BACKGROUND: Surface electromyography (sEMG) signal is the combined effect of superficial muscle EMG and neural electrical activity. In recent years, researchers did large amount of human-machine system studies by using the physiological signals as co...

Modeling Movement Primitives with Hidden Markov Models for Robotic and Biomedical Applications.

Methods in molecular biology (Clifton, N.J.)
Movement primitives are elementary motion units and can be combined sequentially or simultaneously to compose more complex movement sequences. A movement primitive timeseries consist of a sequence of motion phases. This progression through a set of m...

Multiple sensors-based kernel machine learning in smart environment.

The Review of scientific instruments
Sensor-based monitoring systems use multiple sensors to identify high-level information based on the events that take place in a monitored environment. Identification and health care are important tasks in the smart environment. This paper presents a...

Stationary Wavelet Transform and AdaBoost with SVM Based Pathological Brain Detection in MRI Scanning.

CNS & neurological disorders drug targets
This paper presents an automatic classification system for segregating pathological brain from normal brains in magnetic resonance imaging scanning. The proposed system employs contrast limited adaptive histogram equalization scheme to enhance the di...

A Pathological Brain Detection System based on Extreme Learning Machine Optimized by Bat Algorithm.

CNS & neurological disorders drug targets
AIM: It is beneficial to classify brain images as healthy or pathological automatically, because 3D brain images can generate so much information which is time consuming and tedious for manual analysis. Among various 3D brain imaging techniques, magn...

Role of Artificial Intelligence Techniques (Automatic Classifiers) in Molecular Imaging Modalities in Neurodegenerative Diseases.

Current Alzheimer research
Artificial Intelligence (AI) is a very active Computer Science research field aiming to develop systems that mimic human intelligence and is helpful in many human activities, including Medicine. In this review we presented some examples of the exploi...

High-throughput time-stretch imaging flow cytometry for multi-class classification of phytoplankton.

Optics express
Time-stretch imaging has been regarded as an attractive technique for high-throughput imaging flow cytometry primarily owing to its real-time, continuous ultrafast operation. Nevertheless, two key challenges remain: (1) sufficiently high time-stretch...

Label-aligned multi-task feature learning for multimodal classification of Alzheimer's disease and mild cognitive impairment.

Brain imaging and behavior
Multimodal classification methods using different modalities of imaging and non-imaging data have recently shown great advantages over traditional single-modality-based ones for diagnosis and prognosis of Alzheimer's disease (AD), as well as its prod...

Health informatics to optimize complex laboratory developed test configurations.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Configuration of complex Laboratory Developed Tests (LDTs) is a time-consuming and complicated task, potentially leading to inconsistent LDTs in which features constraints remain unresolved and important features could remain unselected.