AIMC Topic: Neural Networks, Computer

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Automatic segmentation of the uterus on MRI using a convolutional neural network.

Computers in biology and medicine
BACKGROUND: This study was performed to evaluate the clinical feasibility of a U-net for fully automatic uterine segmentation on MRI by using images of major uterine disorders.

Machine learning algorithms can classify outdoor terrain types during running using accelerometry data.

Gait & posture
BACKGROUND: Running is a popular physical activity that benefits health; however, running surface characteristics may influence loading impact and injury risk. Machine learning algorithms could automatically identify running surface from wearable mot...

Automatic segmentation of the mandible from computed tomography scans for 3D virtual surgical planning using the convolutional neural network.

Physics in medicine and biology
Segmentation of mandibular bone in CT scans is crucial for 3D virtual surgical planning of craniofacial tumor resection and free flap reconstruction of the resection defect, in order to obtain a detailed surface representation of the bones. A major d...

Automated and Interpretable Patient ECG Profiles for Disease Detection, Tracking, and Discovery.

Circulation. Cardiovascular quality and outcomes
BACKGROUND: The ECG remains the most widely used diagnostic test for characterization of cardiac structure and electrical activity. We hypothesized that parallel advances in computing power, machine learning algorithms, and availability of large-scal...

An approach on the implementation of full batch, online and mini-batch learning on a Mamdani based neuro-fuzzy system with center-of-sets defuzzification: Analysis and evaluation about its functionality, performance, and behavior.

PloS one
Due to the rapid technological evolution and communications accessibility, data generated from different sources of information show an exponential growth behavior. That is, volume of data samples that need to be analyzed are getting larger, so the m...

Protein model accuracy estimation based on local structure quality assessment using 3D convolutional neural network.

PloS one
In protein tertiary structure prediction, model quality assessment programs (MQAPs) are often used to select the final structural models from a pool of candidate models generated by multiple templates and prediction methods. The 3-dimensional convolu...

Barrier Function-Based Adaptive Control for Uncertain Strict-Feedback Systems Within Predefined Neural Network Approximation Sets.

IEEE transactions on neural networks and learning systems
In this article, a globally stable adaptive control strategy for uncertain strict-feedback systems is proposed within predefined neural network (NN) approximation sets, despite the presence of unknown system nonlinearities. In contrast to the convent...

Nonpooling Convolutional Neural Network Forecasting for Seasonal Time Series With Trends.

IEEE transactions on neural networks and learning systems
This article focuses on a problem important to automatic machine learning: the automatic processing of a nonpreprocessed time series. The convolutional neural network (CNN) is one of the most popular neural network (NN) algorithms for pattern recogni...

Neural Probabilistic Graphical Model for Face Sketch Synthesis.

IEEE transactions on neural networks and learning systems
Neural network learning for face sketch synthesis from photos has attracted substantial attention due to its favorable synthesis performance. However, most existing deep-learning-based face sketch synthesis models stacked only by multiple convolution...

A deep learning method for image-based subject-specific local SAR assessment.

Magnetic resonance in medicine
PURPOSE: Local specific absorption rate (SAR) cannot be measured and is usually evaluated by offline numerical simulations using generic body models that of course will differ from the patient's anatomy. An additional safety margin is needed to inclu...