AIMC Topic: Neural Networks, Computer

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MR-based synthetic CT generation using dual-attention enhanced 3D Conditional GAN for head and neck radiotherapy.

Biomedical physics & engineering express
. This study aims to synthesize CT from MR images for radiotherapy planning of head and neck tumor using an improved three-dimensional conditional generative adversarial network (3D cGAN) based on dual-attention modules.. A total of 212 paired CT and...

STF-DKANMixer: Tri-component decomposition with KAN-MLP hybrid architecture for time series forecasting.

PloS one
Long-term time series forecasting is critical for domains such as traffic and energy systems, yet contemporary models often fail to capture complex multiscale patterns and nonlinear dynamics, resulting in significant inaccuracies during periods of ab...

Mechanistic, data-driven, and hybrid models: A critical comparison in surrogate drug dissolution modeling.

International journal of pharmaceutics
Mathematical modeling is becoming increasingly important in the pharmaceutical industry. It supports the Quality by Design framework by aiding process understanding and examining the impact of critical material and process parameters on the critical ...

Neural Network Circuit for Operant Conditioning with Blocking and Overshadowing Effects Based on DNA Strand Displacement.

ACS synthetic biology
Operant conditioning reflects the ability of organisms to adapt and learn. By implementing operant conditioning neural networks, complex brain-like behaviors can be simulated and learned at the molecular level. In this paper, an operant conditioning ...

Uncertainty quantification enables reliable deep learning for protein-ligand binding affinity prediction.

Scientific reports
Deep learning (DL) algorithms have increasingly been applied to predict protein-ligand binding affinity, a critical step in drug design. Yet, many models still struggle to generalize to unseen data, and when coupled with the absence of confidence est...

An automated classification of brain white matter inherited disorders (Leukodystrophy) using MRI image features.

Biomedical physics & engineering express
Leukodystrophies are a group of inherited disorders that predominantly and selectively affect the white matter of the central nervous system. Their overlapping clinical and imaging manifestations make a timely and accurate diagnosis challenging. In t...

Multi-scale dynamic graph neural network for PM2.5 concentration prediction in regional station cluster.

PloS one
Accurate prediction of PM2.5 concentrations is crucial for public health and environmental management. However, effectively capturing complex spatiotemporal dependencies across multiple time scales remains a persistent challenge for existing methods,...

GR-AttNet: Robotic grasping with lightweight spatial attention mechanism.

PloS one
Robotic grasping is crucial in manufacturing, logistics, and service robotics, but existing methods struggle with object occlusion and complex arrangements in cluttered scenes. We propose the Generative Residual Attention Network (GR-AttNet), based o...

Capsule-based federated reinforcement learning adaptive sliding mode for anomaly detection and control of floating wind turbines.

PloS one
Floating wind turbines (FWTs) are now recognized as one of the most effective and affordable renewable energy sources. However, their performance is strongly influenced by dynamic environmental conditions, particularly sea waves under significant osc...

AttentionDriveNet: Fusion of deep cognitive network with Attention modeling for robust navigation in Self-driving vehicles.

PloS one
Self-driving vehicles are envisioned as automated and safety-focused vehicles facilitating smooth movement on roads. This research proposes a novel, robust, and intelligent navigation framework for such vehicles through an integrated fusion of advanc...