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Identifying and Reporting Child abuse

Latest AI and machine learning research in identifying and reporting child abuse for healthcare professionals.

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Counterfactual learning for higher-order relation prediction in heterogeneous information networks.

Heterogeneous Information Networks (HINs) play a crucial role in modeling complex social systems, wh...

Learning soft tissue deformation from incremental simulations.

BACKGROUND: Surgical planning for orthognathic procedures demands swift and accurate biomechanical m...

Signed Curvature Graph Representation Learning of Brain Networks for Brain Age Estimation.

Graph Neural Networks (GNNs) play a pivotal role in learning representations of brain networks for e...

Liver tumor segmentation method combining multi-axis attention and conditional generative adversarial networks.

In modern medical imaging-assisted therapies, manual annotation is commonly employed for liver and t...

PDG2Seq: Periodic Dynamic Graph to Sequence Model for Traffic Flow Prediction.

Traffic flow prediction is the foundation of intelligent traffic management systems. Current methods...

MRI denoising with a non-blind deep complex-valued convolutional neural network.

MR images with high signal-to-noise ratio (SNR) provide more diagnostic information. Various methods...

Air quality index prediction with optimisation enabled deep learning model in IoT application.

The development of industrial and urban places caused air pollution, which has resulted in a variety...

GCLmf: A Novel Molecular Graph Contrastive Learning Framework Based on Hard Negatives and Application in Toxicity Prediction.

In silico methods for prediction of chemical toxicity can decrease the cost and increase the efficie...

Generative artificial intelligence and ethical considerations in health care: a scoping review and ethics checklist.

The widespread use of Chat Generative Pre-trained Transformer (known as ChatGPT) and other emerging ...

A Machine Learning Method for RNA-Small Molecule Binding Preference Prediction.

The interaction between RNA and small molecules is crucial in various biological functions. Identify...

GlobalSR: Global context network for single image super-resolution via deformable convolution attention and fast Fourier convolution.

Vision Transformer have achieved impressive performance in image super-resolution. However, they suf...

Reconstruct incomplete relation for incomplete modality brain tumor segmentation.

Different brain tumor magnetic resonance imaging (MRI) modalities provide diverse tumor-specific inf...

Skeleton-guided multi-scale dual-coordinate attention aggregation network for retinal blood vessel segmentation.

Deep learning plays a pivotal role in retinal blood vessel segmentation for medical diagnosis. Despi...

Towards consensual representation: Model-agnostic knowledge extraction for dual heterogeneous federated fault diagnosis.

Federated fault diagnosis has attracted increasing attention in industrial cloud-edge collaboration ...

CPU-GPU Cooperative QoS Optimization of Personalized Digital Healthcare Using Machine Learning and Swarm Intelligence.

In recent decades, the rapid advances in information technology have promoted a widespread deploymen...

State of the Art of Brain Function Detection Technologies in Robot-Assisted Lower Limb Rehabilitation.

With an aging population, the prevalence of neurological disorders is increasing, leading to a rise...

Meta-Analysis and Machine Learning Models for Anaerobic Biodegradation Rates of Organic Contaminants in Sediments and Sludge.

Anaerobic biodegradation rates (half-lives) of organic chemicals are pivotal for environmental risk ...

Prediction of Human Liver Microsome Clearance with Chirality-Focused Graph Neural Networks.

In drug candidate design, clearance is one of the most crucial pharmacokinetic parameters to conside...

Graph Aggregating-Repelling Network: Do Not Trust All Neighbors in Heterophilic Graphs.

Graph neural networks (GNNs) have demonstrated exceptional performance in processing various types o...

Radial Undersampled MRI Reconstruction Using Deep Learning With Mutual Constraints Between Real and Imaginary Components of K-Space.

The deep learning method is an efficient solution for improving the quality of undersampled magnetic...

Seizure Detection Based on Lightweight Inverted Residual Attention Network.

Timely and accurately seizure detection is of great importance for the diagnosis and treatment of ep...

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