AIMC Topic: Neural Networks, Computer

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Machine Learning Approaches for Predicting Radiation Therapy Outcomes: A Clinician's Perspective.

International journal of radiation oncology, biology, physics Nov 11, 2015
Radiation oncology has always been deeply rooted in modeling, from the early days of isoeffect curves to the contemporary Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) initiative. In recent years, medical modeling for both pr...
Machine Learning Prognosis Lung Neoplasms Logistic Models Reproducibility of Results Humans Neural Networks, Computer Artificial Intelligence Radiotherapy Esophagitis Xerostomia Radiation Pneumonitis Models, Statistical Treatment Outcome Radiation Oncology Support Vector Machine Radiotherapy Dosage
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Enhanced Logical Stochastic Resonance in Synthetic Genetic Networks.

IEEE transactions on neural networks and learning systems Nov 10, 2015
In this brief, the concept of logical stochastic resonance is applied to implement the Set-Reset latch in a synthetic gene network derived from a bacteriophage λ . Clear Set-Reset latch operation is obtained when the network is only subjected to peri...
Bacteriophage lambda Gene Regulatory Networks Stochastic Processes Neural Networks, Computer
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Modeling the motor cortex: Optimality, recurrent neural networks, and spatial dynamics.

Neuroscience research Nov 10, 2015
Specialization of motor function in the frontal lobe was first discovered in the seminal experiments by Fritsch and Hitzig and subsequently by Ferrier in the 19th century. It is, however, ironical that the functional and computational role of the mot...
Neural Networks, Computer Animals Models, Neurological Humans Visual Perception Motor Cortex Electrophysiological Phenomena Psychomotor Performance Movement
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An investigation into the usefulness of different empirical modeling techniques for better control of spray-on fluidized bed melt granulation.

International journal of pharmaceutics Nov 10, 2015
Melt granulation in fluid bed processors is an emerging technique, but literature data regarding the modeling of this granulation method are lacking. In the present study different techniques (response surface analysis, multilayer perceptron neural n...
Chemistry, Pharmaceutical Empirical Research Polyethylene Glycols Viscosity Neural Networks, Computer
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Perceptual discrimination in fear generalization: Mechanistic and clinical implications.

Neuroscience and biobehavioral reviews Nov 10, 2015
For almost a century, Pavlovian conditioning is the imperative experimental paradigm to investigate the development and generalization of fear. However, despite the rich research tradition, the conceptualization of fear generalization has remained so...
Conditioning, Classical Learning Animals Thinking Behavior Fear Humans Neural Networks, Computer
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Stability of discrete time recurrent neural networks and nonlinear optimization problems.

Neural networks : the official journal of the International Neural Network Society Nov 7, 2015
We consider the method of Reduction of Dissipativity Domain to prove global Lyapunov stability of Discrete Time Recurrent Neural Networks. The standard and advanced criteria for Absolute Stability of these essentially nonlinear systems produce rather...
Neurons Nonlinear Dynamics Neural Networks, Computer Algorithms
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Feature Set Evaluation for Offline Handwriting Recognition Systems: Application to the Recurrent Neural Network Model.

IEEE transactions on cybernetics Nov 6, 2015
The performance of handwriting recognition systems is dependent on the features extracted from the word image. A large body of features exists in the literature, but no method has yet been proposed to identify the most promising of these, other than ...
Pattern Recognition, Automated Handwriting Algorithms Databases, Factual Image Processing, Computer-Assisted Humans Neural Networks, Computer
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Learning to Estimate Dynamical State with Probabilistic Population Codes.

PLoS computational biology Nov 5, 2015
Tracking moving objects, including one's own body, is a fundamental ability of higher organisms, playing a central role in many perceptual and motor tasks. While it is unknown how the brain learns to follow and predict the dynamics of objects, it is ...
Humans Neural Networks, Computer Algorithms Models, Neurological Models, Statistical Proprioception Computer Simulation Computational Biology
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Automated Grading of Gliomas using Deep Learning in Digital Pathology Images: A modular approach with ensemble of convolutional neural networks.

AMIA ... Annual Symposium proceedings. AMIA Symposium Nov 5, 2015
Brain glioma is the most common primary malignant brain tumors in adults with different pathologic subtypes: Lower Grade Glioma (LGG) Grade II, Lower Grade Glioma (LGG) Grade III, and Glioblastoma Multiforme (GBM) Grade IV. The survival and treatment...
Glioma Machine Learning Humans Brain Neoplasms Glioblastoma Neural Networks, Computer Image Processing, Computer-Assisted Electronic Data Processing
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Causal Phenotype Discovery via Deep Networks.

AMIA ... Annual Symposium proceedings. AMIA Symposium Nov 5, 2015
The rapid growth of digital health databases has attracted many researchers interested in using modern computational methods to discover and model patterns of health and illness in a research program known as computational phenotyping. Much of the wo...
Physiology Machine Learning Humans Databases, Factual Phenotype Intensive Care Units Neural Networks, Computer Algorithms Critical Illness Disease
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