Public Health & Policy

Personalized surveillance in colorectal cancer: Integrating circulating tumor DNA and artificial intelligence into post-treatment follow-up.

Given the growing burden of colorectal cancer (CRC) as a global health challenge, it becomes imperat...

Predicting overactive bladder from inflammatory markers: A machine learning approach using NHANES 2005-2020.

Overactive bladder (OAB), a prevalent condition characterized by urgency and nocturia, imposes signi...

"What Did You Say, ChatGPT?" The Use of AI in Black Women's HIV Self-Education: An Inductive Qualitative Data Analysis.

The emergence of widely accessible artificial intelligence (AI) chatbots such as ChatGPT presents un...

Machine Learning Techniques Applied to COVID-19 Prediction: A Systematic Literature Review.

COVID-19 was one of the most serious global public health emergencies in recent years, and its extre...

An Interpretable AI for Smart Homes: Identifying Fall Prevention Strategies for Older Adults Using Multimodal Deep Learning.

Falls are a significant cause of mortality among older adults and are considered preventable emergen...

Sex differences in bladder cancer: understanding biological and clinical implications.

Bladder cancer (BC) remains a significant global health concern, with substantial sex and racial dis...

Dual level dengue diagnosis using lightweight multilayer perceptron with XAI in fog computing environment and rule based inference.

Over the last fifty years, arboviral infections have made an unparalleled contribution to worldwide ...

Publisher Correction: A robust and interpretable ensemble machine learning model for predicting healthcare insurance fraud.

OB HUB: Remote Electronic Fetal Monitoring Surveillance.

OBJECTIVE: The purpose of this project was to implement a remote fetal surveillance unit with increa...

Rapid Response System Restructure: Focus on Prevention and Early Intervention.

This article describes the staged restructure of the rapid response program into a dedicated 24/7 pr...

An Anomaly Node Detection Method for Wireless Sensor Networks Based on Deep Metric Learning with Fusion of Spatial-Temporal Features.

Wireless sensor networks (WSNs) use distributed nodes for tasks such as environmental monitoring and...

Evaluating Machine Learning Models for Predicting Late Leprosy Diagnosis by Physical Disability Grade in Brazil (2018-2022).

The severity of physical disability at leprosy diagnosis reflects the timeliness of case detection a...

A deep learning and molecular modeling approach to repurposing Cangrelor as a potential inhibitor of Nipah virus.

Deforestation, urbanization, and climate change have significantly increased the risk of zoonotic di...

Special Issue on CDS Failures: Performance Degradation between Development and Deployment of a Predictive Model for Central-Line Associated Blood Stream Infections in Hospitalized Children.

BACKGROUND: Central line-associated bloodstream infections (CLABSIs) are associated with substantial...

Machine Learning Model for Predicting Coronary Heart Disease Risk: Development and Validation Using Insights From a Japanese Population-Based Study.

BACKGROUND: Coronary heart disease (CHD) is a major cause of morbidity and mortality worldwide. Iden...

Stigma Attitudes Toward HIV/AIDS From 2011 Through 2023 in Japan: Retrospective Study in Japan.

BACKGROUND: Stigma associated with HIV/AIDS continues to be a major barrier to prevention, managemen...

Fusogenic Lipid Nanovesicles as Multifunctional Immunomodulatory Platforms for Precision Solid Tumor Therapy.

Although immunotherapy demonstrates considerable prospect in overcoming solid tumors, its clinical e...

[Surveillance for pneumonia of unknown etiology: current status, challenges, and implementation ways].

The prevention and control of emerging and reemerging infectious diseases are crucial for national b...

[Progress in method development and application of distributed learning for estimation of epidemiological effect].

To systematically review the progress in the method development and application of distributed lear...

Traffic-related air pollution backcasting using convolutional neural network and long short-term memory approach.

Air pollution backcasting, especially nitrogen dioxide (NO), is crucial in epidemiological studies, ...

Exploring the potential biomarkers and potential causality of Ménière disease based on bioinformatics and machine learning.

Meniere disease (MD) is a common inner ear disorder closely related to immune abnormalities, but res...