Public Health & Policy

Unveiling the Threat of Fraud Gangs to Graph Neural Networks: Multi-Target Graph Injection Attacks Against GNN-Based Fraud Detectors

Graph neural networks (GNNs) have emerged as an effective tool for fraud detection, identifying fraudulent users, and uncovering malicious behaviors. However, attacks against GNN-based fraud detectors and their risks have rarely been studied, thereby leaving potential threats unaddressed. Recent findings suggest that frauds are increasingly organized as gangs or groups. In this work, we design a...

[Application of artificial intelligence in parasitic diseases and parasitology].

The rapid development of artificial intelligence poses a huge impact on health and has become a core driving force for the new generation of the scientific and technological revolution in the field of healthcare. Recently, artificial intelligence has been gradually applied in the field of parasitic diseases and parasitology, including disease diagnosis, prognosis prediction, prediction of transmis...

Surveillance Capitalism Revealed: Tracing The Hidden World Of Web Data Collection

This study investigates the mechanisms of Surveillance Capitalism, focusing on personal data transfer during web navigation and searching. Analyzing...

Detecting anxiety and depression in dialogues: a multi-label and explainable approach

Anxiety and depression are the most common mental health issues worldwide, affecting a non-negligible part of the population. Accordingly, stakehold...

Facial Expression Analysis and Its Potentials in IoT Systems: A Contemporary Survey

Facial expressions convey human emotions and can be categorized into macro-expressions (MaEs) and micro-expressions (MiEs) based on duration and int...

Neuromorphic Spiking Neural Network Based Classification of COVID-19 Spike Sequences

The availability of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) virus data post-COVID has reached exponentially to an enormous magn...

Assessing the effectiveness of test-trace-isolate interventions using a multi-layered temporal network

In the early stage of an infectious disease outbreak, public health strategies tend to gravitate towards non-pharmaceutical interventions (NPIs) giv...

Spatio-Temporal SIR Model of Pandemic Spread During Warfare with Optimal Dual-use Healthcare System Administration using Deep Reinforcement Learning

Large-scale crises, including wars and pandemics, have repeatedly shaped human history, and their simultaneous occurrence presents profound challeng...

Cognition Chain for Explainable Psychological Stress Detection on Social Media

Stress is a pervasive global health issue that can lead to severe mental health problems. Early detection offers timely intervention and prevention ...

Physics-Based Adversarial Attack on Near-Infrared Human Detector for Nighttime Surveillance Camera Systems

Many surveillance cameras switch between daytime and nighttime modes based on illuminance levels. During the day, the camera records ordinary RGB im...

Safeguarding Virtual Healthcare: A Novel Attacker-Centric Model for Data Security and Privacy

The rapid growth of remote healthcare delivery has introduced significant security and privacy risks to protected health information (PHI). Analysis...

Future Aspects in Human Action Recognition: Exploring Emerging Techniques and Ethical Influences

Visual-based human action recognition can be found in various application fields, e.g., surveillance systems, sports analytics, medical assistive te...

Unsupervised UAV 3D Trajectories Estimation with Sparse Point Clouds

Compact UAV systems, while advancing delivery and surveillance, pose significant security challenges due to their small size, which hinders detectio...

WaveGNN: Modeling Irregular Multivariate Time Series for Accurate Predictions

Accurately modeling and analyzing time series data is crucial for downstream applications across various fields, including healthcare, finance, astr...

A Cascaded Dilated Convolution Approach for Mpox Lesion Classification

The global outbreak of the Mpox virus, classified as a Public Health Emergency of International Concern (PHEIC) by the World Health Organization, pr...

CAD-Unet: A Capsule Network-Enhanced Unet Architecture for Accurate Segmentation of COVID-19 Lung Infections from CT Images

Since the outbreak of the COVID-19 pandemic in 2019, medical imaging has emerged as a primary modality for diagnosing COVID-19 pneumonia. In clinica...

Fairness in Computational Innovations: Identifying Bias in Substance Use Treatment Length of Stay Prediction Models with Policy Implications

Predictive machine learning (ML) models are computational innovations that can enhance medical decision-making, including aiding in determining opti...

Deep Learning and Hybrid Approaches for Dynamic Scene Analysis, Object Detection and Motion Tracking

This project aims to develop a robust video surveillance system, which can segment videos into smaller clips based on the detection of activities. I...

Multi-scale phylodynamic modelling of rapid punctuated pathogen evolution

Computational multi-scale pandemic modelling remains a major and timely challenge. Here we identify specific requirements for a new class of pandemi...

Interpretable Hierarchical Attention Network for Medical Condition Identification

Accurate prediction of medical conditions with straight past clinical evidence is a long-sought topic in the medical management and health insurance...