AIMC Topic: Algorithms

Clear Filters Showing 3541 to 3550 of 28713 articles

Two algorithms for improving model-based diagnosis using multiple observations and deep learning.

Neural networks : the official journal of the International Neural Network Society
Model-based diagnosis (MBD) is a critical problem in artificial intelligence. Recent advancements have made it possible to address this challenge using methods like deep learning. However, current approaches that use deep learning for MBD often strug...

When bipartite graph learning meets anomaly detection in attributed networks: Understand abnormalities from each attribute.

Neural networks : the official journal of the International Neural Network Society
Detecting anomalies in attributed networks has become a subject of interest in both academia and industry due to its wide spectrum of applications. Although most existing methods achieve desirable performance by the merit of various graph neural netw...

Leveraging labelled data knowledge: A cooperative rectification learning network for semi-supervised 3D medical image segmentation.

Medical image analysis
Semi-supervised 3D medical image segmentation aims to achieve accurate segmentation using few labelled data and numerous unlabelled data. The main challenge in the design of semi-supervised learning methods consists in the effective use of the unlabe...

Multiple token rearrangement Transformer network with explicit superpixel constraint for segmentation of echocardiography.

Medical image analysis
Diagnostic cardiologists have considerable clinical demand for precise segmentation of echocardiography to diagnose cardiovascular disease. The paradox is that manual segmentation of echocardiography is a time-consuming and operator-dependent task. C...

SAF-IS: A spatial annotation free framework for instance segmentation of surgical tools.

Medical image analysis
Instance segmentation of surgical instruments is a long-standing research problem, crucial for the development of many applications for computer-assisted surgery. This problem is commonly tackled via fully-supervised training of deep learning models,...

Gait Video-Based Prediction of Severity of Cerebellar Ataxia Using Deep Neural Networks.

Movement disorders : official journal of the Movement Disorder Society
BACKGROUND: Pose estimation algorithms applied to two-dimensional videos evaluate gait disturbances; however, a few studies have used this method to evaluate ataxic gait.

Interpretable COVID-19 chest X-ray detection based on handcrafted feature analysis and sequential neural network.

Computers in biology and medicine
Deep learning methods have significantly improved medical image analysis, particularly in detecting COVID-19 chest X-rays. Nonetheless, these methodologies frequently inhibit some drawbacks, such as limited interpretability, extensive computational r...

Reinforced Collaborative-Competitive Representation for Biomedical Image Recognition.

Interdisciplinary sciences, computational life sciences
Artificial intelligence technology has demonstrated remarkable diagnostic efficacy in modern biomedical image analysis. However, the practical application of artificial intelligence is significantly limited by the presence of similar pathologies amon...

Identifying candidate RNA-seq biomarkers for severity discrimination in chemical injuries: A machine learning and molecular dynamics approach.

International immunopharmacology
INTRODUCTION: Biomarkers play a crucial role across various fields by providing insights into biological responses to interventions. High-throughput gene expression profiling technologies facilitate the discovery of data-driven biomarkers through ext...

PeptideForest: Semisupervised Machine Learning Integrating Multiple Search Engines for Peptide Identification.

Journal of proteome research
The first step in bottom-up proteomics is the assignment of measured fragmentation mass spectra to peptide sequences, also known as peptide spectrum matches. In recent years novel algorithms have pushed the assignment to new heights; unfortunately, d...