Latest AI and machine learning research in public health & policy for healthcare professionals.
Racial disparities in healthcare expenditures are well-documented, yet the underlying drivers remain complex. This study develops a framework to decompose such disparities through shifts in the distributions of mediating variables, rather than treating race itself as a manipulable exposure. We define disparities as differences in covariate-adjusted outcome distributions across racial groups, and d...
College students face a higher risk of depression than their non-college peers. However, the predictors of depressive symptoms among college students and their relative importance remain inconclusive. This study aimed to develop predictive models for depressive symptoms among Chinese undergraduate students using a four-year longitudinal dataset and to explore the importance ranking of predictive f...
UNLABELLED: â–’: Although chronic pain is common after traumatic SCI, prognostic models have traditionally prioritized clinical injury characteristics, ...
INTRODUCTION: Visual impairment and blindness continue to represent a substantial disease burden in Hungary. According to national epidemiological dat...
Using publicly accessible Reddit posts, we developed a manually annotated dataset for traditional and aspect-based sentiment analysis (ABSA) of cannab...
BACKGROUND: Adherence to guideline-based colonoscopy surveillance intervals remains suboptimal. Large language models (LLMs) show promise for automati...
OBJECTIVE: To develop an artificial intelligence (AI)-aided dual-task gait test model for scalable, high-throughput cognitive impairment screening. DE...
Diabetes mellitus (DM) is an escalating global public health concern, with a rapidly increasing burden in low- and middle-income countries, including ...
Lumpy Skin Disease (LSD), caused by the Lumpy Skin Disease Virus (LSDV), which is a part of the family of Poxviridae, subfamily Chordopoxviridae, and ...
BACKGROUND: Patients with invasive breast cancer (IBC) account for the vast majority of breast cancer cases and exhibit significant heterogeneity; hen...
Over the past 35 years, my work has focused on developing and studying robotic technologies to promote hand and arm recovery after stroke. In this Poi...
PROBLEM: Traditional epidemiological surveillance methods are often limited by delays in reporting and fragmented data systems. Saudi Arabia faces add...
INTRODUCTION: Population cancer screening detects the presence of early-stage disease rather than assessing future disease risk. We evaluated whether ...
The combined effect of traffic-related pollutant mixtures on osteoporosis (OP) remains unclear. This study aimed to evaluate such associations using m...
AIM: To identify and differentiate workload patterns across shifts and to provide evidence for optimizing nursing workforce allocation in emergency de...
OBJECTIVES: Chat Generative Pretrained Transformer (ChatGPT) is a widely adopted tool that can provide immediate parenting guidance. The aim of this s...
The convergence of artificial intelligence (AI) and microbial biosensor technology is transforming pathogen detection, environmental surveillance, ant...
Cancer therapeutics account for a significant proportion of new drug development, reflecting advances in diagnosis, treatment, and disease control. Ho...
BACKGROUND: Over the past century, medical education has undergone a profound transformation, evolving from unregulated apprenticeships into a highly ...
Ageing heterogeneity hampers prevention and care. We used routine biochemical panels and unsupervised learning to identify latent phenotypes in commun...