AIMC Topic: Neural Networks, Computer

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Forecasting Banned Substances: Leveraging GNN and Explainable AI for Sports Anti-Doping.

Studies in health technology and informatics
Ensuring fairness in competitive sports requires robust mechanisms for detecting prohibited substances. Despite established regulations, challenges persist in accurately identifying new and emerging doping agents. This study introduces the use of Gra...

A Medical Decision Support System for Automatic Treatment Plan Generation Using Machine Learning Algorithms.

Studies in health technology and informatics
Due to demographic change, health economics is increasingly focused on the quality of life in advanced age and the associated cost aspects. Dementia is one of the key issues in this area and its efficient treatment will become increasingly relevant i...

Graph Neural Networks for Gleason Grading in Prostate Histopathology Images.

Studies in health technology and informatics
Prostate cancer is a leading cause of cancer-related deaths, with Gleason grading being key for assessing tumor aggressiveness. We propose a Graph Neural Network-based approach to automate Gleason grading using the Automated Gleason Grading Challenge...

EnGCI: enhancing GPCR-compound interaction prediction via large molecular models and KAN network.

BMC biology
BACKGROUND: Identifying GPCR-compound interactions (GCI) plays a significant role in drug discovery and chemogenomics. Machine learning, particularly deep learning, has become increasingly influential in this domain. Large molecular models, due to th...

Artificial intelligence for severity triage based on conversations in an emergency department in Korea.

Scientific reports
In the fast-paced emergency departments, where crises unfold unpredictably, the systematic prioritization of critical patients based on a severity classification is vital for swift and effective treatment. This study aimed to enhance the quality of e...

Ethnic dance movement instruction guided by artificial intelligence and 3D convolutional neural networks.

Scientific reports
This study aims to explore the potential application of artificial intelligence in ethnic dance action instruction and achieve movement recognition by utilizing the three-dimensional convolutional neural networks (3D-CNNs). In this study, the 3D-CNNs...

Research on agricultural disease recognition methods based on very large Kernel convolutional network-RepLKNet.

Scientific reports
Agricultural diseases pose significant challenges to plant production. With the rapid advancement of deep learning, the accuracy and efficiency of plant disease identification have substantially improved. However, conventional convolutional neural ne...

Commonality and individuality based graph learning network for EEG emotion recognition.

Journal of neural engineering
The interplay between individual differences and shared human characteristics significantly impacts electroencephalogram (EEG) emotion recognition models, yet remains underexplored. To address this, we propose a commonality and individuality-based EE...

Prediction of plasma concentration-time profiles in mice using deep neural network integrated with pharmacokinetic models.

International journal of pharmaceutics
Quantitative structure-activity relationship (QSAR) methods have emerged as powerful tools to streamline non-clinical pharmacokinetic (PK) studies, with extensive evidence demonstrating their potential to predict key in vivo PK parameters such as cle...

SERS-ATB: A comprehensive database server for antibiotic SERS spectral visualization and deep-learning identification.

Environmental pollution (Barking, Essex : 1987)
The rapid and accurate identification of antibiotics in environmental samples is critical for addressing the growing concern of antibiotic pollution, particularly in water sources. Antibiotic contamination poses a significant risk to ecosystems and h...