AIMC Topic: Neural Networks, Computer

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An Improved Sparse Representation over Learned Dictionary Method for Seizure Detection.

International journal of neural systems
Automatic seizure detection has played an important role in the monitoring, diagnosis and treatment of epilepsy. In this paper, a patient specific method is proposed for seizure detection in the long-term intracranial electroencephalogram (EEG) recor...

Development of the brain's structural network efficiency in early adolescence: A longitudinal DTI twin study.

Human brain mapping
The brain is a network and our intelligence depends in part on the efficiency of this network. The network of adolescents differs from that of adults suggesting developmental changes. However, whether the network changes over time at the individual l...

Rich spectrum of neural field dynamics in the presence of short-term synaptic depression.

Physical review. E, Statistical, nonlinear, and soft matter physics
In continuous attractor neural networks (CANNs), spatially continuous information such as orientation, head direction, and spatial location is represented by Gaussian-like tuning curves that can be displaced continuously in the space of the preferred...

A Computationally Inexpensive Optimal Guidance via Radial-Basis-Function Neural Network for Autonomous Soft Landing on Asteroids.

PloS one
Optimal guidance is essential for the soft landing task. However, due to its high computational complexities, it is hardly applied to the autonomous guidance. In this paper, a computationally inexpensive optimal guidance algorithm based on the radial...

Neuro-fuzzy classification of asthma and chronic obstructive pulmonary disease.

BMC medical informatics and decision making
BACKGROUND: This paper presents a system for classification of asthma and chronic obstructive pulmonary disease (COPD) based on fuzzy rules and the trained neural network.

Deep Neural Networks with Multistate Activation Functions.

Computational intelligence and neuroscience
We propose multistate activation functions (MSAFs) for deep neural networks (DNNs). These MSAFs are new kinds of activation functions which are capable of representing more than two states, including the N-order MSAFs and the symmetrical MSAF. DNNs w...

Predicting Response to Neoadjuvant Chemotherapy with PET Imaging Using Convolutional Neural Networks.

PloS one
Imaging of cancer with 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) has become a standard component of diagnosis and staging in oncology, and is becoming more important as a quantitative monitor of individual response to therapy....

Temporal stability of network centrality in control and default mode networks: Specific associations with externalizing psychopathology in children and adolescents.

Human brain mapping
Abnormal connectivity patterns have frequently been reported as involved in pathological mental states. However, most studies focus on "static," stationary patterns of connectivity, which may miss crucial biological information. Recent methodological...

Automatic Identification of Human Erythrocytes in Microscopic Fecal Specimens.

Journal of medical systems
Traditional fecal erythrocyte detection is performed via a manual operation that is unsuitable because it depends significantly on the expertise of individual inspectors. To recognize human erythrocytes automatically and precisely, automatic segmenta...