AIMC Topic: Neural Networks, Computer

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Morphometric similarity network-based graph convolutional networks for schizophrenia classification.

Scientific reports
Schizophrenia is a complex neuropsychiatric disorder characterized by significant heterogeneity, posing a challenge for accurate classification using neuroimaging data. Graph convolutional networks (GCNs) have emerged as a promising approach for leve...

A deep learning framework for Ethiopian sign language recognition using skeleton-based representation.

Scientific reports
This study proposes an environment- and signer-invariant sign language recognition model. The model first extracts skeletal key-points from the signer via MediaPipe, which is Google's cross-platform pipeline framework that helps to detect and track h...

Interpretable deep learning for personalized energy expenditure prediction using ECG and acceleration signals in incremental exercise.

Scientific reports
Energy expenditure (EE) assessment is crucial in both sports science and health management. However, current EE prediction models often overlook individual differences and lack dynamic correlation analysis between multi-modal data and EE. Building up...

Convolutional neural network based system for fully automatic FLAIR MRI segmentation in multiple sclerosis diagnosis.

Scientific reports
This study presents an automated system using Convolutional Neural Networks (CNNs) for segmenting FLAIR Magnetic Resonance Imaging (MRI) images to aid in the diagnosis of Multiple Sclerosis (MS). The dataset included 103 patients from Imam Khomeini H...

Predicting sequence-specific amplification efficiency in multi-template PCR with deep learning.

Nature communications
Multi-template polymerase chain reaction (PCR) is a critical technique enabling the parallel amplification of diverse DNA molecules, thereby facilitating applications in fields from quantitative molecular biology to DNA data storage. However, non-hom...

Research on egg yolk color detection based on near infrared spectroscopy and machine vision.

Analytical methods : advancing methods and applications
Yolk color is a key indicator of egg quality, as customers prefer eggs with intensely yellow yolks, which also signal nutrient richness. At present, the commonly used method for yolk color detection is to open the eggs and evaluate the yolk color usi...

MG-DIFF: A novel molecular graph diffusion model for molecular generation and optimization.

PloS one
Recent advancements in denoising diffusion models have revolutionized image, text, and video generation. Inspired by these achievements, researchers have extended denoising diffusion models to the field of molecule generation. However, existing molec...

BONE-Net: A novel hybrid deep-learning model for effective osteoporosis detection.

PloS one
Osteoporosis is a prevalent bone disease characterized by reduced bone density and an elevated risk of fractures, especially in older adults and postmenopausal women. The clinical consequences of osteoporotic fractures extend beyond pain and disabili...

Transfer learning-driven prediction of oil and gaspipeline corrosion rates in small sample scenarios.

PloS one
To ensure the safe operation of oil and gas pipeline systems in complex environments, accurately predicting the corrosion rate of natural gas well pipes is of paramount importance. Given the widespread challenge of pipe corrosion in the oil and gas i...

A physically informed domain-independent data-driven inundation forecast model.

Water research
Inundation maps with spatial and temporal distribution of the water depths are essential for protecting the population in case of pluvial flood events. Creating these maps in operational forecasting is currently not possible with traditional physical...