AIMC Topic: Neural Networks, Computer

Clear Filters Showing 20001 to 20010 of 31376 articles

Towards Robust and Accurate Detection of Abnormalities in Musculoskeletal Radiographs with a Multi-Network Model.

Sensors (Basel, Switzerland)
This study proposes a novel multi-network architecture consisting of a multi-scale convolution neural network (MSCNN) with fully connected graph convolution network (GCN), named MSCNN-GCN, for the detection of musculoskeletal abnormalities via muscul...

Machine-Learning-Based Muscle Control of a 3D-Printed Bionic Arm.

Sensors (Basel, Switzerland)
In this paper, a customizable wearable 3D-printed bionic arm is designed, fabricated, and optimized for a right arm amputee. An experimental test has been conducted for the user, where control of the artificial bionic hand is accomplished successfull...

Emotion recognition with convolutional neural network and EEG-based EFDMs.

Neuropsychologia
Electroencephalogram (EEG), as a direct response to brain activity, can be used to detect mental states and physical conditions. Among various EEG-based emotion recognition studies, due to the non-linear, non-stationary and the individual difference ...

Borrowing external information to improve Bayesian confidence propagation neural network.

European journal of clinical pharmacology
PURPOSE: A Bayesian confidence propagation neural network (BCPNN) is a signal detection method used by the World Health Organization Uppsala Monitoring Centre to analyze spontaneous reporting system databases. We modify the BCPNN to increase its sens...

Integrative blockwise sparse analysis for tissue characterization and classification.

Artificial intelligence in medicine
The topic of sparse representation of samples in high dimensional spaces has attracted growing interest during the past decade. In this work, we develop sparse representation-based methods for classification of clinical imaging patterns into healthy ...

Myocardial infarction evaluation from stopping time decision toward interoperable algorithmic states in reinforcement learning.

BMC medical informatics and decision making
BACKGROUND: The Elliot wave principle commonly characterizes the impulsive and corrective wave trends for both financial market trends and electrocardiograms. The impulsive wave trends of electrocardiograms can annotate several wave components of hea...

Machine learning paradigm for dynamic contrast-enhanced MRI evaluation of expanding bladder.

Frontiers in bioscience (Landmark edition)
Delineation of the bladder under a dynamic contrast enhanced (DCE)-MRI protocol requires robust segmentation. However, this method is subject to errors due to variations in the content of fluid within the bladder, as well as presence of air and simil...

AD-NET: Age-adjust neural network for improved MCI to AD conversion prediction.

NeuroImage. Clinical
The prediction of Mild Cognitive Impairment (MCI) patients who are at higher risk converting to Alzheimer's Disease (AD) is critical for effective intervention and patient selection in clinical trials. Different biomarkers including neuroimaging have...

CM-supplement network model for reducing the memory consumption during multilabel image annotation.

PloS one
With the rapid development of the Internet and the increasing popularity of mobile devices, the availability of digital image resources is increasing exponentially. How to rapidly and effectively retrieve and organize image information has been a hot...

A size-invariant convolutional network with dense connectivity applied to retinal vessel segmentation measured by a unique index.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Retinal vessel segmentation (RVS) helps in diagnosing diseases such as hypertension, cardiovascular diseases, and others. Convolutional neural networks are widely used in RVS tasks. However, how to comprehensively evaluate ...