AIMC Topic: Algorithms

Clear Filters Showing 20531 to 20540 of 28713 articles

Hypergraph-Induced Convolutional Networks for Visual Classification.

IEEE transactions on neural networks and learning systems
At present, convolutional neural networks (CNNs) have become popular in visual classification tasks because of their superior performance. However, CNN-based methods do not consider the correlation of visual data to be classified. Recently, graph con...

Alzheimer's disease diagnosis based on multiple cluster dense convolutional networks.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Alzheimer's disease (AD) is an irreversible neurodegenerative disorder with progressive impairment of memory and cognitive functions. Structural magnetic resonance images (MRI) play important role to evaluate the brain anatomical changes for AD Diagn...

Diagnosis of urinary tract infection based on artificial intelligence methods.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Urinary tract infection (UTI) is a common disease affecting the vast majority of people. UTI involves a simple infection caused by urinary tract inflammation as well as a complicated infection that may be caused by an inflam...

Gene Regulatory Relationship Mining Using Improved Three-Phase Dependency Analysis Approach.

IEEE/ACM transactions on computational biology and bioinformatics
How to mine the gene regulatory relationship and construct gene regulatory network (GRN) is of utmost interest within the whole biological community, however, which has been consistently a challenging problem since the tremendous complexity in cellul...

Non-orthogonal one-step calibration method for robotized transcranial magnetic stimulation.

Biomedical engineering online
BACKGROUND: Robotized transcranial magnetic stimulation (TMS) combines the benefits of neuro-navigation with automation and provides a precision brain stimulation method. Since the coil will normally remain unmounted between different clinical uses, ...

Laplacian mixture modeling for network analysis and unsupervised learning on graphs.

PloS one
Laplacian mixture models identify overlapping regions of influence in unlabeled graph and network data in a scalable and computationally efficient way, yielding useful low-dimensional representations. By combining Laplacian eigenspace and finite mixt...

Reachable set estimation for Markovian jump neural networks with time-varying delay.

Neural networks : the official journal of the International Neural Network Society
This paper is concerned with the reachable set estimation for Markovian jump neural networks with time-varying delay and bounded peak inputs. The objective is to find a description of a reachable set that is containing all reachable states starting f...

ECG authentication system design incorporating a convolutional neural network and generalized S-Transformation.

Computers in biology and medicine
Electrocardiogram (ECG) is gaining increased attention as a biometric method in a wide range of applications, such as access control and security/privacy requirements. The majority of reported investigations using the ECG biometric method are usually...

DrugMetab: An Integrated Machine Learning and Lexicon Mapping Named Entity Recognition Method for Drug Metabolite.

CPT: pharmacometrics & systems pharmacology
Drug metabolites (DMs) are critical in pharmacology research areas, such as drug metabolism pathways and drug-drug interactions. However, there is no terminology dictionary containing comprehensive drug metabolite names, and there is no named entity ...

Exploring spatial-frequency-sequential relationships for motor imagery classification with recurrent neural network.

BMC bioinformatics
BACKGROUND: Conventional methods of motor imagery brain computer interfaces (MI-BCIs) suffer from the limited number of samples and simplified features, so as to produce poor performances with spatial-frequency features and shallow classifiers.