AIMC Topic: Neural Networks, Computer

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Spike detection and sorting with deep learning.

Journal of neural engineering
OBJECTIVE: The extraction and identification of single-unit activities in intracortically recorded electric signals have a key role in basic neuroscience, but also in applied fields, like in the development of high-accuracy brain-computer interfaces....

Multicenter Computer-Aided Diagnosis for Lymph Nodes Using Unsupervised Domain-Adaptation Networks Based on Cross-Domain Confounding Representations.

Computational and mathematical methods in medicine
To achieve the robust high-performance computer-aided diagnosis systems for lymph nodes, CT images may be typically collected from multicenter data, which cause the isolated performance of the model based on different data source centers. The variabi...

Research of Multimodal Medical Image Fusion Based on Parameter-Adaptive Pulse-Coupled Neural Network and Convolutional Sparse Representation.

Computational and mathematical methods in medicine
Visual effects of medical image have a great impact on clinical assistant diagnosis. At present, medical image fusion has become a powerful means of clinical application. The traditional medical image fusion methods have the problem of poor fusion re...

Observer-independent assessment of psoriasis-affected area using machine learning.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: Assessment of psoriasis severity is strongly observer-dependent, and objective assessment tools are largely missing. The increasing number of patients receiving highly expensive therapies that are reimbursed only for moderate-to-severe ps...

l-l state estimation for delayed artificial neural networks under high-rate communication channels with Round-Robin protocol.

Neural networks : the official journal of the International Neural Network Society
In this paper, the l-l state estimation problem is addressed for a class of delayed artificial neural networks under high-rate communication channels with Round-Robin (RR) protocol. To estimate the state of the artificial neural networks, numerous se...

Medi-Care AI: Predicting medications from billing codes via robust recurrent neural networks.

Neural networks : the official journal of the International Neural Network Society
In this paper, we present an effective deep prediction framework based on robust recurrent neural networks (RNNs) to predict the likely therapeutic classes of medications a patient is taking, given a sequence of diagnostic billing codes in their reco...

Application of Deep Learning Convolutional Neural Networks for Internal Tablet Defect Detection: High Accuracy, Throughput, and Adaptability.

Journal of pharmaceutical sciences
Tablet defects encountered during the manufacturing of oral formulations can result in quality concerns, timeline delays, and elevated financial costs. Internal tablet cracking is not typically measured in routine inspections but can lead to batch fa...

Neural hierarchical models of ecological populations.

Ecology letters
Neural networks are increasingly being used in science to infer hidden dynamics of natural systems from noisy observations, a task typically handled by hierarchical models in ecology. This article describes a class of hierarchical models parameterise...

Adaptive predictive systems applied to gait analysis: A systematic review.

Gait & posture
BACKGROUND: Due to the high susceptivity of the walking pattern to be affected by several disorders, accurate analysis methods are necessary. Given the complexity and relevance of such assessment, the utilization of methods to facilitate it plays a s...

Fast contour propagation for MR-guided prostate radiotherapy using convolutional neural networks.

Medical physics
PURPOSE: To quickly and automatically propagate organ contours from pretreatment to fraction images in magnetic resonance (MR)-guided prostate external-beam radiotherapy.