AIMC Topic: Deep Learning

Clear Filters Showing 251 to 260 of 27298 articles

Ultrasound derived deep learning features for predicting axillary lymph node metastasis in breast cancer using graph convolutional networks in a multicenter study.

Scientific reports
The purpose of this study was to create and validate an ultrasound-based graph convolutional network (US-based GCN) model for the prediction of axillary lymph node metastasis (ALNM) in patients with breast cancer. A total of 820 eligible patients wit...

An optimized multi-scale dilated attention layer for keratoconus disease classification.

International ophthalmology
INTRODUCTION: Keratoconus (KCN) is a progressive and non-inflammatory corneal disorder characterized by thinning and conical deformation of the cornea, resulting in visual impairment. Early and accurate detection is crucial to prevent disease progres...

Low-cost computation for isolated sign language video recognition with multiple reservoir computing.

PloS one
Sign language recognition (SLR) has the potential to bridge communication gaps and empower hearing-impaired communities. To ensure the portability and accessibility of the SLR system, its implementation on a portable, server-independent device become...

Divide-and-conquer routing for learning heterogeneous individualized capsules.

PloS one
Capsule Networks (CapsNets) have demonstrated an enhanced ability to capture spatial relationships and preserve hierarchical feature representations compared to Convolutional Neural Networks (CNNs). However, the dynamic routing mechanism in CapsNets ...

Investigating the impact of social media images on users' sentiments towards sociopolitical events based on deep artificial intelligence.

PloS one
This paper presents the findings of the research aimed at investigating the influence of visual content, posted on social media in shaping users' sentiments towards specific sociopolitical events. The study analyzed various sociopolitical topics by e...

Knee osteoarthritis prediction from gait kinematics: Exploring the potential of deep neural networks and transfer learning methods for time series classification.

Journal of biomechanics
Recent advances in artificial intelligence methods have allowed improved disease diagnosis using fast and low-cost protocols. The present study explored the potential of different deep neural networks (DNNs) and transfer learning methods to detect kn...

SpaSEG: unsupervised deep learning for multi-task analysis of spatially resolved transcriptomics.

Genome biology
Spatially resolved transcriptomics (SRT) for characterizing spatial cellular heterogeneities in tissue environments requires systematic analytical approaches to elucidate gene expression variations within their physiological context. Here, we introdu...

Multiple Tumor-related autoantibodies test enhances CT-based deep learning performance in diagnosing lung cancer with diameters < 70 mm: a prospective study in China.

BMC pulmonary medicine
BACKGROUND: Deep learning (DL) demonstrates high sensitivity but low specificity in lung cancer (LC) detection during CT screening, and the seven Tumor-associated antigens autoantibodies (7-TAAbs), known for its high specificity in LC, was employed t...

Nondestructive freshness recognition of chicken breast meat based on deep learning.

Scientific reports
Identifying chicken breast freshness is an important component of poultry food safety. Traditional methods for chicken breast freshness recognition suffer from issues such as high cost, difficulty in recognition, and low efficiency. In this study, th...

A multimodal deep learning architecture for predicting interstitial glucose for effective type 2 diabetes management.

Scientific reports
The accurate prediction of blood glucose is critical for the effective management of diabetes. Modern continuous glucose monitoring (CGM) technology enables real-time acquisition of interstitial glucose concentrations, which can be calibrated against...