AIMC Topic: Neural Networks, Computer

Clear Filters Showing 2881 to 2890 of 31376 articles

Chemical Space Networks Enhance Toxicity Recognition via Graph Embedding.

Journal of chemical information and modeling
Chemical space networks (CSNs) are a new effective strategy for detecting latent chemical patterns irrespective of defined coordinate systems based on molecular descriptors and fingerprints. CSNs can be a new powerful option as a new approach method ...

CL-GNN: Contrastive Learning and Graph Neural Network for Protein-Ligand Binding Affinity Prediction.

Journal of chemical information and modeling
In the realm of drug discovery and design, the accurate prediction of protein-ligand binding affinity is of paramount importance as it underpins the functional interactions within biological systems. This study introduces a novel self-supervised lear...

MSCMamba: Prediction of Antimicrobial Peptide Activity Values by Fusing Multiscale Convolution with Mamba Module.

The journal of physical chemistry. B
Antimicrobial peptides (AMPs) have important developmental prospects as potential candidates for novel antibiotics. Although many studies have been devoted to the identification of AMPs and the qualitative prediction of their functional activities, f...

Deep learning-driven bacterial cytological profiling to determine antimicrobial mechanisms in .

Proceedings of the National Academy of Sciences of the United States of America
Tuberculosis (TB), caused by , remains a significant global health threat, affecting an estimated 10.6 million people in 2022. The emergence of multidrug resistant and extensively drug resistant strains necessitates the development of novel and effec...

Prediction of circRNA-Disease Associations via Graph Isomorphism Transformer and Dual-Stream Neural Predictor.

Biomolecules
Circular RNAs (circRNAs) have attracted increasing attention for their roles in human diseases, making the prediction of circRNA-disease associations (CDAs) a critical research area for advancing disease diagnosis and treatment. However, traditional ...

Intelligent Microfluidics for Plasma Separation: Integrating Computational Fluid Dynamics and Machine Learning for Optimized Microchannel Design.

Biosensors
Efficient separation of blood plasma and Packed Cell Volume (PCV) is vital for rapid blood sensing and early disease detection, especially in point-of-care and resource-limited environments. Conventional centrifugation methods for separation are reso...

Sorghum yield prediction based on remote sensing and machine learning in conflict affected South Sudan.

Scientific reports
Sorghum cultivation plays a pivotal role in addressing food insecurity in South Sudan, but persistent conflict continues to impose challenges in the agriculture sector therefore understanding the impact of conflict on sorghum yield prediction is impo...

Continuous implicit neural representation for arbitrary super-resolution of system matrix in magnetic particle imaging.

Physics in medicine and biology
. Magnetic particle imaging (MPI) is a novel imaging technique that uses magnetic fields to detect tracer materials consisting of magnetic nanoparticles. System matrix (SM) based image reconstruction is essential for achieving high image quality in M...

Improved U-Net based on ResNet and SE-Net with dual attention mechanism for glottis semantic segmentation.

Medical engineering & physics
In previous tasks of glottis image segmentation, the position attention mechanism was rarely incorporated, neglecting the detailed information in glottis position detection. Aiming to improve the U-Net architecture, this study introduces the dual att...

Knowledge Distillation Guided Interpretable Brain Subgraph Neural Networks for Brain Disorder Exploration.

IEEE transactions on neural networks and learning systems
The human brain is a highly complex neurological system that has been the subject of continuous exploration by scientists. With the help of modern neuroimaging techniques, there has been significant progress made in brain disorder analysis. There is ...