AIMC Topic: Algorithms

Clear Filters Showing 9621 to 9630 of 28713 articles

A simple and reliable instance selection for fast training support vector machine: Valid Border Recognition.

Neural networks : the official journal of the International Neural Network Society
Support vector machines (SVMs) are powerful statistical learning tools, but their application to large datasets can cause time-consuming training complexity. To address this issue, various instance selection (IS) approaches have been proposed, which ...

Fixed-time periodic stabilization of discontinuous reaction-diffusion Cohen-Grossberg neural networks.

Neural networks : the official journal of the International Neural Network Society
This paper aims to study the fixed-time stabilization of a class of delayed discontinuous reaction-diffusion Cohen-Grossberg neural networks. Firstly, by providing some relaxed conditions containing indefinite functions and based on inequality techni...

Safe screening rules for multi-view support vector machines.

Neural networks : the official journal of the International Neural Network Society
Multi-view learning aims to make use of the advantages of different views to complement each other and fully mines the potential information in the data. However, the complexity of multi-view learning algorithm is much higher than that of single view...

Toward safer ophthalmic artificial intelligence via distributed validation on real-world data.

Current opinion in ophthalmology
PURPOSE OF REVIEW: The current article provides an overview of the present approaches to algorithm validation, which are variable and largely self-determined, as well as solutions to address inadequacies.

Artificial intelligence for predicting acute appendicitis: a systematic review.

ANZ journal of surgery
BACKGROUND: Paediatric appendicitis may be challenging to diagnose, and outcomes difficult to predict. While diagnostic and prognostic scores exist, artificial intelligence (AI) may be able to assist with these tasks.

Efficient machine learning of solute segregation energy based on physics-informed features.

Scientific reports
Machine learning models solute segregation energy based on appropriate features of segregation sites. Lumping many features together can give a decent accuracy but may suffer the curse of dimensionality. Here, we modeled the segregation energy with e...

Active learning for prediction of tensile properties for material extrusion additive manufacturing.

Scientific reports
Machine learning techniques were used to predict tensile properties of material extrusion-based additively manufactured parts made with Technomelt PA 6910, a hot melt adhesive. An adaptive data generation technique, specifically an active learning pr...

Systematical analysis of underlying markers associated with Marfan syndrome via integrated bioinformatics and machine learning strategies.

Journal of biomolecular structure & dynamics
Marfan syndrome (MFS) is a hereditary disease with high mortality. This study aimed to explore peripheral blood potential markers and underlying mechanisms in MFS via a series bioinformatics and machine learning analysis. First, we downloaded two MFS...

An unsupervised two-step training framework for low-dose computed tomography denoising.

Medical physics
BACKGROUND: Although low-dose computed tomography (CT) imaging has been more widely adopted in clinical practice to reduce radiation exposure to patients, the reconstructed CT images tend to have more noise, which impedes accurate diagnosis. Recently...