AIMC Topic: Algorithms

Clear Filters Showing 14561 to 14570 of 28713 articles

The Role of Machine Learning in Cardiovascular Pathology.

The Canadian journal of cardiology
Machine learning has seen slow but steady uptake in diagnostic pathology over the past decade to assess digital whole-slide images. Machine learning tools have incredible potential to standardise, and likely even improve, histopathologic diagnoses, b...

External validation of a commercially available deep learning algorithm for fracture detection in children.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to conduct an external validation of a fracture assessment deep learning algorithm (Rayvolve®) using digital radiographs from a real-life cohort of children presenting routinely to the emergency room.

Inter-patient automated arrhythmia classification: A new approach of weight capsule and sequence to sequence combination.

Computer methods and programs in biomedicine
OBJECTIVE: We propose a new capsule network to compensate for the information loss in the deep convolutional networks in previous studies, and to improve the performance of arrhythmia classification.

A novel design of Gudermannian function as a neural network for the singular nonlinear delayed, prediction and pantograph differential models.

Mathematical biosciences and engineering : MBE
The present work is to solve the nonlinear singular models using the framework of the stochastic computing approaches. The purpose of these investigations is not only focused to solve the singular models, but the solution of these models will be pres...

Machine learning approach for predicting the antifungal effect of gilaburu (Viburnum opulus) fruit extracts on Fusarium spp. isolated from diseased potato tubers.

Journal of microbiological methods
This work addresses the mathematical model building to detect the diameter of the inhibition zone of gilaburu (Viburnum opulus L.) extract against eight different Fusarium strains isolated from diseased potato tubers. Gilaburu extracts were obtained ...

Automatic liver tumor localization using deep learning-based liver boundary motion estimation and biomechanical modeling (DL-Bio).

Medical physics
PURPOSE: Recently, two-dimensional-to-three-dimensional (2D-3D) deformable registration has been applied to deform liver tumor contours from prior reference images onto estimated cone-beam computed tomography (CBCT) target images to automate on-board...

Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning.

Sensors (Basel, Switzerland)
Following the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept ...

Epileptic Seizures Detection in EEG Signals Using Fusion Handcrafted and Deep Learning Features.

Sensors (Basel, Switzerland)
Epilepsy is a brain disorder disease that affects people's quality of life. Electroencephalography (EEG) signals are used to diagnose epileptic seizures. This paper provides a computer-aided diagnosis system (CADS) for the automatic diagnosis of epil...

A Novel Complete-Surface-Finding Algorithm for Online Surface Scanning with Limited View Sensors.

Sensors (Basel, Switzerland)
Robotised Non-Destructive Testing (NDT) has revolutionised the field, increasing the speed of repetitive scanning procedures and ability to reach hazardous environments. Application of robot-assisted NDT within specific industries such as remanufactu...

An Efficient and Robust Star Identification Algorithm Based on Neural Networks.

Sensors (Basel, Switzerland)
A lost-in-space star identification algorithm based on a one-dimensional Convolutional Neural Network (1D CNN) is proposed. The lost-in-space star identification aims to identify stars observed with corresponding catalog stars when there is no prior ...