AIMC Topic: Neural Networks, Computer

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Multi-task deep learning for predicting metabolic syndrome from retinal fundus images in a Japanese health checkup dataset.

PloS one
BACKGROUND: Retinal fundus images provide a noninvasive window into systemic health, offering opportunities for early detection of metabolic disorders such as metabolic syndrome (METS).

Multilevel Fusion Graph Neural Network for Molecule Property Prediction.

Journal of chemical information and modeling
Accurate prediction of molecular properties is essential in drug discovery and related fields. However, existing graph neural networks (GNNs) often struggle to simultaneously capture both local and global molecular structures. In this work, we propos...

Visual language transformer framework for multimodal dance performance evaluation and progression monitoring.

Scientific reports
Dance is often perceived as complex due to the need for coordinating multiple body movements and precisely aligning them with musical rhythm and content. Research in automatic dance performance assessment has the potential to enhance individuals' sen...

A study on the effectiveness of machine learning models for hepatitis prediction.

Scientific reports
Hepatitis continues to be a major global health challenge, leading to high morbidity and mortality rates. Despite advances in diagnosis and treatment, early prediction of hepatitis outcomes remains an essential area for improvement. This study seeks ...

Accurate modeling and simulation of the effect of bacterial growth on the pH of culture media using artificial intelligence approaches.

Scientific reports
This research investigates the impact of bacterial growth on the pH of culture media, emphasizing its significance in microbiological and biotechnological applications. A range of sophisticated artificial intelligence methods, including One-Dimension...

Interpretable deep learning method to quantify the impact of extreme temperatures on vegetation productivity in China.

Scientific reports
As a key ecological parameter, NPP measures the photosynthetic efficiency of plants in capturing atmospheric carbon. With the warming of the climate, extreme temperature events are frequent, which has exerted a profound influence on NPP. Previous stu...

Computational optimization of 3D printed bone scaffolds using orthogonal array-driven FEA and neural network modeling.

Scientific reports
Today, orthopedic surgeons have been continuously focusing on bone tissue engineering for regenerating damaged bone through the use of biomimetic scaffolds and innovative materials. Hence, this study presents a comprehensive investigation into the op...

A dynamic examination of the digital circuit implementing the Fitzhugh-Nagumo neuron model with emphasis on low power consumption and high precision.

PloS one
Neuromorphic computing has got more attention in various tasks during recent years. The main goal of this field is to explore neural functionality in the brain. The studies of spiking neurons and Spiking Neural Networks (SNNs) are vital to understand...

Deep learning-based spatial analysis on tumor and immune cells of pathology images predicts MIBC prognosis.

PloS one
OBJECTIVE: Muscle-invasive bladder cancer (MIBC) is a highly aggressive disease with a poor prognosis. This study aims to explore the correlation between the spatial distribution of lymphocyte aggregates and the prognosis of MIBC using deep learning.

MMFi-DPBML: Multi-molecular fingerprint feature fusion for predicting ingredient-target interactions in traditional Chinese medicine.

Journal of ethnopharmacology
RESEARCH PURPOSE: This study proposes MMFi-DPBML, a deep learning framework that in-tegrates multi-molecular fingerprint features for predicting ingredient-target interactions (ITIs) in traditional Chinese medicine (TCM). By capturing di-verse struct...