Neural Networks (Computer)
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Subject Areas on Research
- A Three-Threshold Learning Rule Approaches the Maximal Capacity of Recurrent Neural Networks.
- A comparison of neural network models for the prediction of the cost of care for acute coronary syndrome patients.
- A comparison of three techniques for rapid model development: an application in patient risk-stratification.
- A constrained optimization approach to preserving prior knowledge during incremental training.
- A continuous attractor network model without recurrent excitation: maintenance and integration in the head direction cell system.
- A framework for integrating the songbird brain.
- A model of visually-guided smooth pursuit eye movements based on behavioral observations.
- A neural network approach to breast cancer diagnosis as a constraint satisfaction problem.
- A neural network model to predict lung radiation-induced pneumonitis.
- A neural network to predict symptomatic lung injury.
- A neural network-based method for spectral distortion correction in photon counting x-ray CT.
- A novel memristive multilayer feedforward small-world neural network with its applications in PID control.
- A robust framework to predict mercury speciation in combustion flue gases.
- A strategy for the rapid identification of phosphorylation sites in the phosphoproteome.
- Acute pulmonary embolism: artificial neural network approach for diagnosis.
- Acute pulmonary embolism: cost-effectiveness analysis of the effect of artificial neural networks on patient care.
- Acute urinary retention: who is at risk and how best to manage it?
- Adaptive feedback control by constrained approximate dynamic programming.
- Adaptive prediction of internal target motion using external marker motion: a technical study.
- An artificial neural network approach to quantitative single photon emission computed tomographic reconstruction with collimator, attenuation, and scatter compensation.
- An artificial neural network for estimating scatter exposures in portable chest radiography.
- An artificial neural network for lesion detection on single-photon emission computed tomographic images.
- Analysis and minimization of overtraining effect in rule-based classifiers for computer-aided diagnosis.
- Analyzing animal behavior via classifying each video frame using convolutional neural networks.
- Applications of neural networks in urologic oncology.
- Artificial neural network for diagnosis of acute pulmonary embolism: effect of case and observer selection.
- Artificial neural network model of survival in patients treated with irradiation with and without concurrent chemotherapy for advanced carcinoma of the head and neck.
- Artificial neural network-based glaucoma diagnosis using retinal nerve fiber layer analysis.
- Artificial neural network: improving the quality of breast biopsy recommendations.
- Artificial neural networks for single photon emission computed tomography. A study of cold lesion detection and localization.
- Artificial neural networks improve the accuracy of cancer survival prediction.
- Automated computerized scheme for distinction between benign and malignant solitary pulmonary nodules on chest images.
- Automatic Feature Learning to Grade Nuclear Cataracts Based on Deep Learning.
- Available space and extracellular transport of macromolecules: effects of pore size and connectedness.
- Beam-orientation customization using an artificial neural network.
- Breast cancer: prediction with artificial neural network based on BI-RADS standardized lexicon.
- Breast mass lesions: computer-aided diagnosis models with mammographic and sonographic descriptors.
- Case-based reasoning computer algorithm that uses mammographic findings for breast biopsy decisions.
- Circuit design and exponential stabilization of memristive neural networks.
- Combination of multiple serum markers using an artificial neural network to improve specificity in discriminating malignant from benign pelvic masses.
- Combining location and expression data for principled discovery of genetic regulatory network models.
- Combining multiple models to generate consensus: application to radiation-induced pneumonitis prediction.
- Combining multiple serum tumor markers improves detection of stage I epithelial ovarian cancer.
- Combining natural language processing and network analysis to examine how advocacy organizations stimulate conversation on social media.
- Comparative study of machine-learning and chemometric tools for analysis of in-vivo high-throughput screening data.
- Computation in neural systems. Editorial.
- Computer simulations of morphologically reconstructed CA3 hippocampal neurons.
- Computer-aided diagnosis in chest radiography: results of large-scale observer tests at the 1996-2001 RSNA scientific assemblies.
- Computer-aided diagnosis in chest radiology.
- Computer-aided diagnosis of breast cancer: artificial neural network approach for optimized merging of mammographic features.
- Computer-aided diagnostic scheme for the detection of lung nodules on chest radiographs: localized search method based on anatomical classification.
- Contributions of intrinsic membrane dynamics to fast network oscillations with irregular neuronal discharges.
- Correlations between synapses in pairs of neurons slow down dynamics in randomly connected neural networks.
- Cross-institutional evaluation of BI-RADS predictive model for mammographic diagnosis of breast cancer.
- Daniel Amit (1938-2007).
- Data mining methods find demographic predictors of preterm birth.
- Deep Learning to Classify Radiology Free-Text Reports.
- Deep learning for segmentation of brain tumors: Impact of cross-institutional training and testing.
- Differences between computer-aided diagnosis of breast masses and that of calcifications.
- Dynamics and plasticity of stimulus-selective persistent activity in cortical network models.
- Effect of patient history data on the prediction of breast cancer from mammographic findings with artificial neural networks.
- Effects of synaptic connectivity on liquid state machine performance.
- Effects of wide band inhibitors in the dorsal cochlear nucleus. II. Model calculations of the responses to complex sounds.
- Efficient supervised learning in networks with binary synapses.
- Exact inferences in a neural implementation of a hidden Markov model.
- Familiarity Detection is an Intrinsic Property of Cortical Microcircuits with Bidirectional Synaptic Plasticity.
- Fast global oscillations in networks of integrate-and-fire neurons with low firing rates.
- Geometric diffusions for the analysis of data from sensor networks.
- Glaucoma detection based on deep convolutional neural network.
- Global exponential synchronization of memristor-based recurrent neural networks with time-varying delays.
- How connectivity, background activity, and synaptic properties shape the cross-correlation between spike trains.
- How noise affects the synchronization properties of recurrent networks of inhibitory neurons.
- Impact of missing data in evaluating artificial neural networks trained on complete data.
- Improved noninvasive diagnosis of acute pulmonary embolism with optimally selected clinical and chest radiographic findings.
- Independent component analyses for quantifying neuronal ensemble interactions.
- Insights from a simple expression for linear fisher information in a recurrently connected population of spiking neurons.
- Interpreting spatial and temporal neural activity through a recurrent neural network brain-machine interface.
- Is cortical connectivity optimized for storing information?
- Joint modeling of DNA sequence and physical properties to improve eukaryotic promoter recognition.
- Learning receptive fields using predictive feedback.
- Lesion size quantification in SPECT using an artificial neural network classification approach.
- MChip, a low density microarray, differentiates among seasonal human H1N1, North American swine H1N1, and the 2009 pandemic H1N1.
- Memristor crossbar-based neuromorphic computing system: a case study.
- Model of global spontaneous activity and local structured activity during delay periods in the cerebral cortex.
- Multifractal texture analysis of perfusion lung scans as a potential diagnostic tool for acute pulmonary embolism.
- Multiscale approximation with hierarchical radial basis functions networks.
- Neural network analysis identifies scaffold properties necessary for in vitro chondrogenesis in elastin-like polypeptide biopolymer scaffolds.
- Neural network analysis of quantitative histological factors to predict pathological stage in clinical stage I nonseminomatous testicular cancer.
- Nonlinear feedforward networks with stochastic outputs: infomax implies redundancy reduction.
- On the maximization of information flow between spiking neurons.
- On the origin of chaos in autonomous Boolean networks.
- Optimal information storage and the distribution of synaptic weights: perceptron versus Purkinje cell.
- Optimal properties of analog perceptrons with excitatory weights.
- Outcome analysis of patients with acute pancreatitis by using an artificial neural network.
- PATTERN: Pain Assessment for paTients who can't TEll using Restricted Boltzmann machiNe.
- Parameter optimization of a computer-aided diagnosis scheme for the segmentation of microcalcification clusters in mammograms.
- Perceptron error surface analysis: a case study in breast cancer diagnosis.
- Perceptual learning as improved probabilistic inference in early sensory areas.
- Plasticity of directional place fields in a model of rodent CA3.
- Practical outcomes of applying ensemble machine learning classifiers to High-Throughput Screening (HTS) data analysis and screening.
- Predicting breast cancer invasion with artificial neural networks on the basis of mammographic features.
- Prediction of breast cancer malignancy using an artificial neural network.
- Prediction of lupus nephritis in patients with systemic lupus erythematosus using artificial neural networks.
- Predictive model for the diagnosis of intraabdominal abscess.
- Probabilistic population codes and the exponential family of distributions.
- Probabilistic population codes for Bayesian decision making.
- Proper staging techniques in testicular cancer patients.
- Quantitative computerized analysis of diffuse lung disease in high-resolution computed tomography.
- Relative contributions of local cell and passing fiber activation and silencing to changes in thalamic fidelity during deep brain stimulation and lesioning: a computational modeling study.
- Respiratory signal prediction based on adaptive boosting and multi-layer perceptron neural network.
- Retrospective and prospective persistent activity induced by Hebbian learning in a recurrent cortical network.
- Robustness of a neural network model for differencing.
- Screening of hyaluronic acid-poly(ethylene glycol) composite hydrogels to support intervertebral disc cell biosynthesis using artificial neural network analysis.
- Self-organizing map for cluster analysis of a breast cancer database.
- Semantic priming in a cortical network model.
- Slow stochastic Hebbian learning of classes of stimuli in a recurrent neural network.
- Smooth function approximation using neural networks.
- Some features of the spread of epidemics and information on a random graph.
- Storing structured sparse memories in a multi-modular cortical network model.
- The effect of data sampling on the performance evaluation of artificial neural networks in medical diagnosis.
- The interaction of bayesian priors and sensory data and its neural circuit implementation in visually guided movement.
- The statistics of repeating patterns of cortical activity can be reproduced by a model network of stochastic binary neurons.
- Training neural network classifiers for medical decision making: the effects of imbalanced datasets on classification performance.
- Two types of afferent terminals innervate cochlear inner hair cells in C57BL/6J mice.
- Ultrasound Image Discrimination between Benign and Malignant Adnexal Masses Based on a Neural Network Approach.
- Understanding the relationships between spike rate and delta/gamma frequency bands of LFPs and EEGs using a local cortical network model.
- Use of MindMapper software for research domain mapping.
- Using neural networks as an aid in the determination of disease status: comparison of clinical diagnosis to neural-network predictions in a pedigree with autosomal dominant limb-girdle muscular dystrophy.
- What determines the frequency of fast network oscillations with irregular neural discharges? I. Synaptic dynamics and excitation-inhibition balance.
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Keywords of People
- Berchuck, Andrew, James M. Ingram Professor of Gynecologic Oncology, Obstetrics and Gynecology, Gynecologic Oncology
- Craig, Stephen L, William T. Miller Professor of Chemistry, Duke University Energy Initiative
- Farsiu, Sina, Associate Professor in the Department of Biomedical Engineering, Electrical and Computer Engineering
- Hartemink, Alexander J., Professor in the Department of Computer Science, Biology
- Hsu-Kim, Heileen, Mary Milus Yoh and Harold L. Yoh, Jr. Associate Professor of Civil and Environmental Engineering, Civil and Environmental Engineering
- Nicolelis, Miguel Angelo L., Duke School of Medicine Professor in Neuroscience, Biomedical Engineering
- Sullivan, Daniel Carl, Professor Emeritus of Radiology, Radiology
- West, Vivian L, Clinical Associate in the School of Nursing, School of Nursing