AIMC Topic: Neural Networks, Computer

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Predicting genes associated with ossification of the posterior longitudinal ligament using graph attention network.

Methods (San Diego, Calif.)
Ossification of the posterior longitudinal ligament is a degenerative disease that severely impacts the spine, with a complex pathogenesis involving the interplay of multiple genes. This study utilizes a combination of graph neural networks and deep ...

Coronary p-Graph: Automatic classification and localization of coronary artery stenosis from Cardiac CTA using DSA-based annotations.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Coronary artery disease (CAD) is a prevalent cardiovascular condition with profound health implications. Digital subtraction angiography (DSA) remains the gold standard for diagnosing vascular disease, but its invasiveness and procedural demands unde...

HEPOM: Using Graph Neural Networks for the Accelerated Predictions of Hydrolysis Free Energies in Different pH Conditions.

Journal of chemical information and modeling
Hydrolysis is a fundamental family of chemical reactions where water facilitates the cleavage of bonds. The process is ubiquitous in biological and chemical systems, owing to water's remarkable versatility as a solvent. However, accurately predicting...

Interpretable Multiscale Convolutional Neural Network for Classification and Feature Visualization of Weak Raman Spectra of Biomolecules at Cell Membranes.

ACS sensors
Raman spectroscopy in biological applications faces challenges due to complex spectra, characterized by peaks of varying widths and significant biological background noise. Convolutional neural networks (CNNs) are widely used for spectrum classificat...

Artificial neural networks applied to somatosensory evoked potentials for migraine classification.

The journal of headache and pain
BACKGROUND: Finding a biomarker to diagnose migraine remains a significant challenge in the headache field. Migraine patients exhibit dynamic and recurrent alterations in the brainstem-thalamo-cortical loop, including reduced thalamocortical activity...

An effective PO-RSNN and FZCIS based diabetes prediction and stroke analysis in the metaverse environment.

Scientific reports
Chronic disease (CD) like diabetes and stroke impacts global healthcare extensively, and continuous monitoring and early detection are necessary for effective management. The Metaverse Environment (ME) has gained attention in the digital healthcare e...

Wild horseshoe crab image denoising based on CNN-transformer architecture.

Scientific reports
The natural habitats of wild horseshoe crabs (such as beaches, shallow water areas, and intertidal sediments) are complex, posing challenges for image capture, which is often affected by real noise factors. Deep learning models are widely used in ima...

Predicting determinants of unimproved water supply in Ethiopia using machine learning analysis of EDHS-2019 data.

Scientific reports
Over 2 billion people worldwide are impacted by the global dilemma of access to clean and safe drinking water. The problem is most acute in low-income nations, where many people still use unimproved water sources such as exposed wells and surface wat...

Artificial intelligence-based non-invasive bilirubin prediction for neonatal jaundice using 1D convolutional neural network.

Scientific reports
Neonatal jaundice, characterized by elevated bilirubin levels causing yellow discoloration of the skin and eyes in newborns, is a critical condition requiring accurate and timely diagnosis. This study proposes a novel approach using 1D Convolutional ...

A fine-tuned convolutional neural network model for accurate Alzheimer's disease classification.

Scientific reports
Alzheimer's disease (AD) is one of the primary causes of dementia in the older population, affecting memories, cognitive levels, and the ability to accomplish simple activities gradually. Timely intervention and efficient control of the disease prove...