AIMC Topic: Neural Networks, Computer

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Quantum Machine Learning in Drug Discovery: Applications in Academia and Pharmaceutical Industries.

Chemical reviews
The nexus of quantum computing and machine learning─quantum machine learning─offers the potential for significant advancements in chemistry. This Review specifically explores the potential of quantum neural networks on gate-based quantum computers wi...

Application of Mask R-CNN for automatic recognition of teeth and caries in cone-beam computerized tomography.

BMC oral health
OBJECTIVES: Deep convolutional neural networks (CNNs) are advancing rapidly in medical research, demonstrating promising results in diagnosis and prediction within radiology and pathology. This study evaluates the efficacy of deep learning algorithms...

Modeling eye gaze velocity trajectories using GANs with spectral loss for enhanced fidelity.

Scientific reports
Accurate modeling of eye gaze dynamics is essential for advancement in human-computer interaction, neurological diagnostics, and cognitive research. Traditional generative models like Markov models often fail to capture the complex temporal dependenc...

UANV: UNet-based attention network for thoracolumbar vertebral compression fracture angle measurement.

Scientific reports
Kyphosis is a prevalent spinal condition where the spine curves in the sagittal plane, resulting in spine deformities. Curvature estimation provides a powerful index to assess the deformation severity of scoliosis. In current clinical diagnosis, the ...

Personalized deep neural networks reveal mechanisms of math learning disabilities in children.

Science advances
Learning disabilities affect a substantial proportion of children worldwide, with far-reaching consequences for their academic, professional, and personal lives. Here we develop digital twins-biologically plausible personalized deep neural networks (...

Emotion recognition with multiple physiological parameters based on ensemble learning.

Scientific reports
Emotion recognition is a key research area in artificial intelligence, playing a critical role in enhancing human-computer interaction and optimizing user experience design. This study explores the application and effectiveness of ensemble learning m...

Spatial reasoning via recurrent neural dynamics in mouse retrosplenial cortex.

Nature neuroscience
From visual perception to language, sensory stimuli change their meaning depending on previous experience. Recurrent neural dynamics can interpret stimuli based on externally cued context, but it is unknown whether they can compute and employ interna...

Fusing multisensory signals across channels and time.

PLoS computational biology
Animals continuously combine information across sensory modalities and time, and use these combined signals to guide their behaviour. Picture a predator watching their prey sprint and screech through a field. To date, a range of multisensory algorith...

The application of deep learning in economic analysis and marketing strategy formulation in the tourism industry.

PloS one
The tourism industry is ever-evolving in nature, as it operates in a global marketplace that has become progressively global and offers great potential due to technological advances. The tourism industry faces challenges in accurately forecasting eco...

MTGNN: A Drug-Target-Disease Triplet Association Prediction Model Based on Multimodal Heterogeneous Graph Neural Networks and Direction-Aware Metapaths.

Journal of chemical information and modeling
The forecasting of drug-target interactions (DTIs) is a crucial element in the domain of drug repositioning. Current methodologies, primarily based on dual-branch architectures or graph neural networks (GNNs), typically model binary associations─spec...