AIMC Topic: Algorithms

Clear Filters Showing 8951 to 8960 of 28713 articles

SPACEL: deep learning-based characterization of spatial transcriptome architectures.

Nature communications
Spatial transcriptomics (ST) technologies detect mRNA expression in single cells/spots while preserving their two-dimensional (2D) spatial coordinates, allowing researchers to study the spatial distribution of the transcriptome in tissues; however, j...

Plant leaf infected spot segmentation using robust encoder-decoder cascaded deep learning model.

Network (Bristol, England)
Leaf infection detection and diagnosis at an earlier stage can improve agricultural output and reduce monetary costs. An inaccurate segmentation may degrade the accuracy of disease classification due to some different and complex leaf diseases. Also,...

Learning to deep learning: statistics and a paradigm test in selecting a UNet architecture to enhance MRI.

Magma (New York, N.Y.)
OBJECTIVE: This study aims to assess the statistical significance of training parameters in 240 dense UNets (DUNets) used for enhancing low Signal-to-Noise Ratio (SNR) and undersampled MRI in various acquisition protocols. The objective is to determi...

Machine learning algorithms for the prognostication of abdominal aortic aneurysm progression: a systematic review.

Minerva surgery
INTRODUCTION: Abdominal aortic aneurysm (AAA), often characterized by an abdominal aortic diameter over 3.0 cm, is managed through screening, surveillance, and surgical intervention. AAA growth can be heterogeneous and rupture carries a high mortalit...

A novel evolutionary combination of artificial intelligence algorithm and machine learning for landslide susceptibility mapping in the west of Iran.

Environmental science and pollution research international
Detecting and mapping landslides are crucial for effective risk management and planning. With the great progress achieved in applying optimized and hybrid methods, it is necessary to use them to increase the accuracy of landslide susceptibility maps....

Digital image analysis and artificial intelligence in pathology diagnostics-the Swiss view.

Pathologie (Heidelberg, Germany)
Digital pathology (DP) is increasingly entering routine clinical pathology diagnostics. As digitization of the routine caseload advances, implementation of digital image analysis algorithms and artificial intelligence tools becomes not only attainabl...

Clustering Methods for Vibro-Acoustic Sensing Features as a Potential Approach to Tissue Characterisation in Robot-Assisted Interventions.

Sensors (Basel, Switzerland)
This article provides a comprehensive analysis of the feature extraction methods applied to vibro-acoustic signals (VA signals) in the context of robot-assisted interventions. The primary objective is to extract valuable information from these signal...

Novel Wearable HD-EMG Sensor With Shift-Robust Gesture Recognition Using Deep Learning.

IEEE transactions on biomedical circuits and systems
In this work, we present a hardware-software solution to improve the robustness of hand gesture recognition to confounding factors in myoelectric control. The solution includes a novel, full-circumference, flexible, 64-channel high-density electromyo...

Re-UNet: a novel multi-scale reverse U-shape network architecture for low-dose CT image reconstruction.

Medical & biological engineering & computing
In recent years, the growing awareness of public health has brought attention to low-dose computed tomography (LDCT) scans. However, the CT image generated in this way contains a lot of noise or artifacts, which make increasing researchers to investi...

Facemap: a framework for modeling neural activity based on orofacial tracking.

Nature neuroscience
Recent studies in mice have shown that orofacial behaviors drive a large fraction of neural activity across the brain. To understand the nature and function of these signals, we need better computational models to characterize the behaviors and relat...