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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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Showing 379-399 of 2,753 articles
Automatic State Machine Inference for Binary Protocol Reverse Engineering

Protocol Reverse Engineering (PRE) is used to analyze protocols by inferring their structure and b...

Cross-Attention Head Position Patterns Can Align with Human Visual Concepts in Text-to-Image Generative Models

Recent text-to-image diffusion models leverage cross-attention layers, which have been effectively...

Rethinking Cognition: Morphological Info-Computation and the Embodied Paradigm in Life and Artificial Intelligence

This study aims to place Lorenzo Magnanis Eco-Cognitive Computationalism within the broader contex...

Anatomy-Guided Radiology Report Generation with Pathology-Aware Regional Prompts

Radiology reporting generative AI holds significant potential to alleviate clinical workloads and ...

Nanosecond Precision Time Synchronization for Optical Data Center Networks

Optical data center networks (DCNs) are renovating the infrastructure design for the cloud in the ...

Ctrl-GenAug: Controllable Generative Augmentation for Medical Sequence Classification

In the medical field, the limited availability of large-scale datasets and labor-intensive annotat...

Contrasformer: A Brain Network Contrastive Transformer for Neurodegenerative Condition Identification

Understanding neurological disorder is a fundamental problem in neuroscience, which often requires...

FODA-PG for Enhanced Medical Imaging Narrative Generation: Adaptive Differentiation of Normal and Abnormal Attributes

Automatic Medical Imaging Narrative generation aims to alleviate the workload of radiologists by p...

Harnessing the Power of Machine Learning and Electronic Health Records to Support Child Abuse and Neglect Identification in Emergency Department Settings.

Emergency departments (EDs) are pivotal in detecting child abuse and neglect, but this task is often...

Aug 2024 39176527
GACL: Graph Attention Collaborative Learning for Temporal QoS Prediction

Accurate prediction of temporal QoS is crucial for maintaining service reliability and enhancing u...

CAPE: a deep learning framework with Chaos-Attention net for Promoter Evolution.

Predicting the strength of promoters and guiding their directed evolution is a crucial task in synth...

Jul 2024 39120645
MODRL-TA:A Multi-Objective Deep Reinforcement Learning Framework for Traffic Allocation in E-Commerce Search

Traffic allocation is a process of redistributing natural traffic to products by adjusting their p...

TAU-DI Net: A Multi-Scale Convolutional Network Combining Prob-Sparse Attention for EEG-based Depression Identification.

EEG-based detection of major depression disorder (MDD) plays a pivotal role in the subsequent treatm...

Jul 2024 40039164
ClinicalLab: Aligning Agents for Multi-Departmental Clinical Diagnostics in the Real World

LLMs have achieved significant performance progress in various NLP applications. However, LLMs sti...

LLM4MSR: An LLM-Enhanced Paradigm for Multi-Scenario Recommendation

As the demand for more personalized recommendation grows and a dramatic boom in commercial scenari...

Personalized Federated Knowledge Graph Embedding with Client-Wise Relation Graph

Federated Knowledge Graph Embedding (FKGE) has recently garnered considerable interest due to its ...

Medication Recommendation via Dual Molecular Modalities and Multi-Step Enhancement

Existing works based on molecular knowledge neglect the 3D geometric structure of molecules and fa...

GEMF: a novel geometry-enhanced mid-fusion network for PLA prediction.

Accurate prediction of protein-ligand binding affinity (PLA) is important for drug discovery. Recent...

May 2024 38980371
Approximating Nonlinear Functions With Latent Boundaries in Low-Rank Excitatory-Inhibitory Spiking Networks.

Deep feedforward and recurrent neural networks have become successful functional models of the brain...

Apr 2024 38658028
Integrative approach for predicting drug-target interactions via matrix factorization and broad learning systems.

In the drug discovery process, time and costs are the most typical problems resulting from the exper...

Jan 2024 38454698
Automatic recognition of white blood cell images with memory efficient superpixel metric GNN: SMGNN.

An automatic recognizing system of white blood cells can assist hematologists in the diagnosis of ma...

Jan 2024 38454678
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