Identifying and Reporting Child abuse

A unified model of short- and long-term plasticity: Effects on network connectivity and information capacity.

Activity-dependent synaptic plasticity is a fundamental learning mechanism that shapes the connectivity and activity of neural circuits. Existing computational models of Spike-Timing-Dependent Plasticity (STDP) capture long-term synaptic changes with varying degrees of biological detail. A common approach is to neglect the influence of short-term dynamics on long-term plasticity, which may be an o...

Privacy-preserving intrusion detection in IoT smart homes using a federated hybrid 1D-CNN-LSTM model with explainable AI.

The proliferation of Internet of Things (IoT) devices in smart home environments has dramatically expanded the attack surface for cyber threats, particularly botnet-driven Distributed Denial of Service (DDoS) attacks. Centralized Intrusion Detection Systems (IDS) are ill-suited to this domain because they violate user privacy, introduce single points of failure, and incur prohibitive communication...

Retrieval-Augmented Representation for Semi-Supervised Medical Image Segmentation.

Semi-supervised learning (SSL) offers a promising solution to reduce annotation costs in medical image segmentation. Recent text-enhanced SSL methods ...

The promise and peril of AI for disability health equity: A justice-centered narrative review.

Despite the promising potential of Artificial Intelligence (AI) models to enhance health equities for persons with disabilities, poorly designed appli...

Super-resolution MRI and 2.5D deep learning for intratumoral-peritumoral radiomics in preoperative prediction of rectal cancer perineural invasion.

OBJECTIVES: Preoperative prediction of perineural invasion (PNI) in rectal cancer (RC) is challenging due to limited MRI resolution and the neglect of...

Effects of Type and Timing of Clinician-Facing AI Support on Patient Trust in Medical Consultations: 2 Vignette Experiments.

BACKGROUND: AI-based clinical decision support systems are increasingly integrated into medical practice, creating hybrid decision-making processes in...

Livestock Multi-Omics Integration: A Systematic Framework From Statistical Association to Causal Interpretation.

Livestock multi-omics integration is key to unraveling complex trait regulation, yet systematic, livestock-specific strategies remain scarce. This rev...

Stepwise Diagnostic Evaluation of Chinese Large Language Models: Comparative Study of Common and Rare Diseases.

BACKGROUND: Large language models (LLMs) are increasingly applied in clinical decision support, yet their diagnostic performance in Chinese-language s...

Measures matter: assessing childhood maltreatment and emotion dysregulation in a transdiagnostic sample.

Background: Childhood maltreatment (CM) is a major risk factor for different mental disorders and transdiagnostic mechanisms, including emotion dysreg...

PRISM: Prior-enhanced Inference for Spatial Transcriptomic Cell Type Mapping.

MOTIVATION: Cell type annotation in spatial transcriptomics (ST) is fundamental for deciphering complex tissue organization and spatially resolved bio...

AI interventions in cancer screening: balancing equity and cost-effectiveness.

This paper examines the integration of artificial intelligence (AI) into cancer screening programmes, focusing on the associated equity challenges and...

GATESynergy: Integrating Molecular Global-Local Aggregator and Hierarchical Gene-Gated Encoder for Drug Synergy Prediction.

Combination drug therapy is an effective approach to combating drug resistance and enhancing therapeutic efficacy in complex diseases such as cancer. ...

Enhancing pharmaceutical hazard assessment with machine learning mobility models.

Assessing the environmental mobility of pharmaceuticals is critical for robust chemical hazard assessment, yet experimental sorption data are often li...

Conversational AI for Child Abuse Detection Through Multistage Counseling: Model Development and Validation Study.

BACKGROUND: Child abuse severely disrupts the healthy growth and development of children, resulting in long-term physical as well as emotional consequ...

Threat in Frequency: Unveiling Hidden Attack Surfaces by Exploiting Stealthy Backdoors on Diffusion Models.

Diffusion models have emerged as state-of-the-art generative models, capable of producing high-quality synthetic outputs. These generated contents ser...

IPGMVL: based on interactive progressive graph convolution with multi-view learning traffic flow forecasting.

The key challenge in traffic flow prediction lies in modeling complex spatio-temporal dependencies effectively. While graph neural networks have shown...

Dynamic functional graph-Laplacian priors integrated with optimization for EEG source localization.

OBJECTIVE: Electroencephalography (EEG) source localization is an ill-posed inverse problem in which conventional methods often rely on static anatomi...

MAFR-UNet: multi-scale adaptive feature reassembly network for aortic CTA segmentation.

The combinations of Convolutional Neural Networks (CNNs) and Transformer have shown promising results in many medical image segmentation tasks. Howeve...

Data-Driven Exploration and Insights Into Temperature-Dependent Phonons in Inorganic Materials.

Phonons, quantized vibrations of the atomic lattice, are central to thermal transport, structural stability, and phase behavior in crystalline solids....

Multi-chaotic signal identification employing a causal cross-correlation neural network.

Chaos identification plays a crucial role in comprehending complex systems. However, current methods face three challenges: neglect temporal causality...