AIMC Topic: Neural Networks, Computer

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Collection of Simulated Data from a Thalamocortical Network Model.

Neuroinformatics
A major challenge in experimental data analysis is the validation of analytical methods in a fully controlled scenario where the justification of the interpretation can be made directly and not just by plausibility. In some sciences, this could be a ...

Parallel Computing for Brain Simulation.

Current topics in medicinal chemistry
BACKGROUND: The human brain is the most complex system in the known universe, it is therefore one of the greatest mysteries. It provides human beings with extraordinary abilities. However, until now it has not been understood yet how and why most of ...

SpineCreator: a Graphical User Interface for the Creation of Layered Neural Models.

Neuroinformatics
There is a growing requirement in computational neuroscience for tools that permit collaborative model building, model sharing, combining existing models into a larger system (multi-scale model integration), and are able to simulate models using a va...

Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs.

JAMA
IMPORTANCE: Deep learning is a family of computational methods that allow an algorithm to program itself by learning from a large set of examples that demonstrate the desired behavior, removing the need to specify rules explicitly. Application of the...

Adaptive Neural Network Control for the Trajectory Tracking of the Furuta Pendulum.

IEEE transactions on cybernetics
The purpose of this paper is to introduce a novel adaptive neural network-based control scheme for the Furuta pendulum, which is a two degree-of-freedom underactuated system. Adaptation laws for the input and output weights are also provided. The pro...

A fuzzy neural network sliding mode controller for vibration suppression in robotically assisted minimally invasive surgery.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: It is very important for robotically assisted minimally invasive surgery to achieve a high-precision and smooth motion control. However, the surgical instrument tip will exhibit vibration caused by nonlinear friction and unmodeled dynamic...

Mass detection in digital breast tomosynthesis: Deep convolutional neural network with transfer learning from mammography.

Medical physics
PURPOSE: Develop a computer-aided detection (CAD) system for masses in digital breast tomosynthesis (DBT) volume using a deep convolutional neural network (DCNN) with transfer learning from mammograms.

A neural network prediction of environmental determinants of Anopheles sinensis knockdown resistance mutation to pyrethroids in China.

Journal of vector ecology : journal of the Society for Vector Ecology
Selection pressure caused by long-term intensive use of insecticides is the key driving force in resistance development. Additional parameters such as environmental conditions may affect both the mosquito response to insecticides and the selection of...

Imaging and machine learning techniques for diagnosis of Alzheimer's disease.

Reviews in the neurosciences
Alzheimer's disease (AD) is a common health problem in elderly people. There has been considerable research toward the diagnosis and early detection of this disease in the past decade. The sensitivity of biomarkers and the accuracy of the detection t...