AIMC Topic: Neural Networks, Computer

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Deep learning-assisted flavonoid-based fluorescent sensor array for the nondestructive detection of meat freshness.

Food chemistry
Gas sensors containing indicators have been widely used in meat freshness testing. However, concerns about the toxicity of indicators have prevented their commercialization. Here, we prepared three fluorescent sensors by complexing each flavonoid (fi...

Echoes of images: multi-loss network for image retrieval in vision transformers.

Medical & biological engineering & computing
This paper introduces a novel approach to enhance content-based image retrieval, validated on two benchmark datasets: ISIC-2017 and ISIC-2018. These datasets comprise skin lesion images that are crucial for innovations in skin cancer diagnosis and tr...

Attributed Multi-Order Graph Convolutional Network for Heterogeneous Graphs.

Neural networks : the official journal of the International Neural Network Society
Heterogeneous graph neural networks play a crucial role in discovering discriminative node embeddings and relations from multi-relational networks. One of the key challenges in heterogeneous graph learning lies in designing learnable meta-paths, whic...

Performance of different machine learning algorithms in identifying undiagnosed diabetes based on nonlaboratory parameters and the influence of muscle strength: A cross-sectional study.

Journal of diabetes investigation
AIMS/INTRODUCTION: Machine learning algorithms based on the artificial neural network (ANN), support vector machine, naive Bayesian or logistic regression model are commonly used to identify diabetes. This study investigated which approach performed ...

Pattern classification of interstitial lung diseases from computed tomography images using a ResNet-based network with a split-transform-merge strategy and split attention.

Physical and engineering sciences in medicine
In patients with interstitial lung disease (ILD), accurate pattern assessment from their computed tomography (CT) images could help track lung abnormalities and evaluate treatment efficacy. Based on excellent image classification performance, convolu...

Classification of multi-feature fusion ultrasound images of breast tumor within category 4 using convolutional neural networks.

Medical physics
BACKGROUND: Breast tumor is a fatal threat to the health of women. Ultrasound (US) is a common and economical method for the diagnosis of breast cancer. Breast imaging reporting and data system (BI-RADS) category 4 has the highest false-positive valu...

Colorful image reconstruction from neuromorphic event cameras with biologically inspired deep color fusion neural networks.

Bioinspiration & biomimetics
Neuromorphic event-based cameras communicate transients in luminance instead of frames, providing visual information with a fine temporal resolution, high dynamic range and high signal-to-noise ratio. Enriching event data with color information allow...

High-spatial resolution ground-level ozone in Yunnan, China: A spatiotemporal estimation based on comparative analyses of machine learning models.

Environmental research
Monitoring ground-level ozone concentrations is a critical aspect of atmospheric environmental studies. Given the existing limitations of satellite data products, especially the lack of ground-level ozone characterization, and the discontinuity of gr...

Hip contact forces can be predicted with a neural network using only synthesised key points and electromyography in people with hip osteoarthritis.

Osteoarthritis and cartilage
OBJECTIVE: To develop and validate a neural network to estimate hip contact forces (HCF), and lower body kinematics and kinetics during walking in individuals with hip osteoarthritis (OA) using synthesised anatomical key points and electromyography. ...

The role of cell-free DNA biomarkers and patient data in the early prediction of preeclampsia: an artificial intelligence model.

American journal of obstetrics and gynecology
BACKGROUND: Accurate individualized assessment of preeclampsia risk enables the identification of patients most likely to benefit from initiation of low-dose aspirin at 12 to 16 weeks of gestation when there is evidence for its effectiveness, and ena...