Public Health & Policy

Progress in the application research of cervical cancer screening developed by artificial intelligence in large populations.

Cervical cancer stands out among various cancers due to its potential for prevention and eradication, mainly through vaccination and proactive screening measures. However, there are still a large number of women in low- and middle-income countries who need to undergo cervical cancer screening. Conventional cervical cancer screening approaches possess distinct benefits and drawbacks regarding sensi...

School-Based Online Surveillance of Youth: Systematic Search and Content Analysis of Surveillance Company Websites.

BACKGROUND: School-based online surveillance of students has been widely adopted by middle and high school administrators over the past decade. Little is known about the technology companies that provide these services or the benefits and harms of the technology for students. Understanding what information online surveillance companies monitor and collect about students, how they do it, and if and...

Enhancing stroke risk prediction through class balancing and data augmentation with CBDA-ResNet50.

Accurate prediction of stroke risk at an early stage is essential for timely intervention and prevention, especially given the serious health conseque...

Citywide metagenomic surveillance of food centres reveals local microbial signatures and antibiotic resistance gene enrichment.

The distribution of microorganisms in built environments with high human traffic, such as food centres, can potentially have a significant impact on p...

Artificial intelligence and digital twins for the personalised prediction of hypertension risk.

Hypertension is a significant global health challenge, contributing substantially to morbidity and mortality through its association with various card...

Construction of extra-large scale screening tools for risks of severe mental illnesses using real world healthcare data.

IMPORTANCE: The prevalence of severe mental illnesses (SMIs) in the United States is approximately 3 % of the whole population. The ability to conduct...

From combination early detection to multicancer testing: shifting cancer care toward proactive prevention and interception.

Identifying the presence of tumors at a very early stage or deciphering the process underlying their development can enable the interception of pro-ma...

Harnessing technology for hope: a systematic review of digital suicide prevention tools.

This systematic review scrutinizes digital interventions in suicide prevention, telehealth, mobile applications, artificial intelligence (AI), and dig...

Development and evaluation of machine learning training strategies for neonatal mortality prediction using multicountry data.

Neonatal mortality poses a critical challenge in global health, particularly in low- and middle-income countries. Leveraging advancements in technolog...

A hybrid ARIMA-BP approach for superior accuracy in predicting traffic accident losses.

Accurately predicting losses resulting from traffic accidents holds crucial significance for accident prevention. Traffic accident forecasting faces c...

Coupling wastewater-based epidemiology with data-driven machine learning for managing public health risks.

Traditional health surveillance methods play a critical role in public health safety but are limited by the data collection speed, coverage, and resou...

A Multi-kernel CNN model with attention mechanism for classification of citrus plants diseases.

One of the primary challenges leading to a significant reduction in agricultural production is the prevalence of diseases affecting citrus plants. Pre...

Evolving Role of Artificial Intelligence in Endoscopic Management of Inflammatory Bowel Disease: Diagnosis, Surveillance, and Assessment.

Inflammatory bowel disease (IBD), including Crohn's disease and ulcerative colitis, presents substantial diagnostic and management challenges because ...

Automated identification of spotted-fever tick vectors using convolutional neural networks.

Ticks are key ectoparasites for the One Health approach, as they are vectors of pathogens that infect humans, domestic and wild animals. The bacteria ...

A model based on artificial intelligence for the prediction, prevention and patient-centred approach for non-communicable diseases related to metabolic syndrome.

Metabolic syndrome (MetS) is related to non-communicable diseases (NCDs) such as type 2 diabetes (T2D), metabolic-associated steatotic liver disease (...

Developing Nationwide Estimates of Built Environment Quality Characteristics Using Street-View Imagery and Computer Vision.

Environmental health studies commonly rely on urban composition measures for built environment exposure assessment. However, quality measures are equa...

Deep learning-driven insights into the transmission dynamics of hepatitis B virus with treatment.

Viral infections have spread globally, profoundly affecting social and economic aspects of life and causing widespread suffering. Infection caused by ...

Smart-Plexer 2.0: Leveraging New Features of Amplification Curves to Enhance the Selection of Multiplex PCR Assays in Multi-Target Identification.

Multiplex PCR plays a critical role in diagnostics by enabling the detection of multiple targets in a single reaction. However, its use is often limit...

[Applications, challenges and a trustworthy use of artificial intelligence in public health].

The rapid advancements in artificial intelligence (AI) over recent years have resulted in its integration into people's everyday lives. The wide avail...

A deep learning model for early diagnosis of alzheimer's disease combined with 3D CNN and video Swin transformer.

Alzheimer's disease (AD) constitutes a neurodegenerative disorder predominantly observed in the geriatric population. If AD can be diagnosed early, bo...