Latest AI and machine learning research in public health for healthcare professionals.
Accurate forecasting of infectious disease cases and deaths is crucial for public health decision-making. Traditional statistical and machine learning approaches may be challenged by complex temporal patterns and heterogeneous surveillance data. We evaluated large language models (LLMs) for infectious disease forecasting. We collected monthly reported cases and deaths data from China National Noti...
BACKGROUND: The global COVID-19 vaccine rollout faces challenges from persistent hesitancy, especially in rural and underserved regions. Alaska's unique geographic, cultural, and infrastructural challenges create complex dynamics for vaccine uptake. OBJECTIVE: This study uses machine learning on survey data to identify key sociodemographic and attitudinal predictors of hesitancy, informing targete...
Antimicrobial resistance (AMR) is increasingly recognised as a One Health challenge in which environmental reservoirs play an important role in the pe...
BACKGROUND: Physical activity among adults with disabilities is influenced by functional limitations, health status, and socioeconomic conditions; yet...
Acinetobacter baumannii is a critical multidrug-resistant pathogen causing severe healthcare infections with high mortality, yet no licensed vaccine e...
Vibrio cholerae thrives at the interface between the aquatic environment and the human host dynamically through integration of environmental signals t...
Transfusion medicine has practiced a form of precision medicine for decades through compatibility testing, infectious disease screening, component man...
Antimicrobial resistance in aquaculture threatens environmental and public health, but the risk of ARGs cannot be inferred from abundance alone; host ...
Maize streak virus, a cause of maize streak disease, poses a major threat to food security that significantly reduces yields of maize, a crucial food ...
OBJECTIVES: To update and revalidate the Cyber Paranoia and Fear Scale to reflect current technological contexts and examine its relevance to digital ...
BACKGROUND: As coronavirus disease 2019 (COVID-19) has transitioned into an endemic phase characterized by sustained transmission and widespread hybri...
BACKGROUND: Neoantigens-tumor-specific peptides generated by somatic mutations-are central targets of effective anticancer T cell immunity and underpi...
Rising water temperatures and intensifying lake heatwaves (LHWs) are increasingly recognized as important drivers of cyanobacterial harmful algal bloo...
Active surveillance (AS) is widely used for men with low-risk and selected favorable intermediate-risk prostate cancer, but pathways remain heterogene...
BACKGROUND: Post-progression survival (PPS) is a critical endpoint in oncology, yet predictors of PPS and data-driven strategies for post-progression ...
INTRODUCTION: Molecular diagnostics focusing on the detection and analysis of nucleic acids, are indispensable tools for early pathogen identification...
Messenger RNA-lipid nanoparticle (mRNA-LNP) therapeutics have emerged as a versatile drug modality, enabling in vivo protein expression for vaccines, ...
OBJECTIVE: To benchmark zero-shot generative pre-trained transformer (GPT)-based multimodal large language models (MLLMs) for pressure injury (PI) sta...
Using an appropriate mathematical model, this study aims to examine the transmission dynamics and optimal control of hepatitis B virus spreading, empl...
BACKGROUND: Black lung disease remains a major occupational health problem among coal miners and is frequently diagnosed at an advanced stage, limitin...