Latest AI and machine learning research in public health for healthcare professionals.
BACKGROUND: Mild cognitive impairment (MCI) is an important public health concern in ageing populations, yet scalable approaches for early identification in community settings remain limited. Existing prediction studies in China have often relied on questionnaire-based or conventional epidemiological variables, whereas multidomain models incorporating objective behavioural and environmental measur...
PURPOSE: Surveillance of arboviral vectors and screening for probable infection is very important for the planning of vector control programs, especially in countries where these activities are just beginning. In the present study, we conducted mosquito surveillance at 26 locations predicted to be at risk (according to our recently published study using Machine learning) in the Marrakech-Safi regi...
Metabolic biomarkers offer promising opportunities for lung cancer risk assessment and early detection. This study aimed to identify metabolites with ...
BACKGROUND: Pakistan faces a serious challenge in malnutrition, as its core nutrition indicators and minimum dietary diversity remain below the recomm...
Hereditary endocrine neoplastic syndromes require structured, lifelong surveillance owing to their multisystem involvement, variable penetrance, and h...
Virulent bacteriophages (phages) can kill bacterial prey, potentially reducing burden of infection. In cholera, a high phage to Vibrio cholerae ratio ...
Burn injuries are associated with significant morbidity and mortality, largely driven by infectious complications. Disruption of the skin barrier, sys...
OBJECTIVES: Driving under the influence of cannabis is a growing public health concern in the United States. Existing surveillance systems often lack ...
Fungal infections are an increasing global public health concern yet remain underprioritized because of persistent challenges in diagnosis, treatment,...
Despite advances in pharmacotherapy, approximately one-third of individuals with epilepsy develop drug-resistant epilepsy (DRE), accounting for a disp...
BACKGROUND: Active surveillance (AS) is the first-line approach for desmoid-type fibromatosis (DTF). However, 30 % of patients require active treatmen...
PURPOSE OF REVIEW: Generative artificial intelligence, particularly large language models, has emerged as a promising tool for processing the vast amo...
AIM: To evaluate the performance of machine learning models in predicting liver metastasis in colorectal cancer (CRC) patients using the SEER database...
Emerging global health threats, from antimicrobial resistance to vector-borne diseases, require scalable diagnostic solutions. Matrix-assisted laser d...
Food-safety occurrence databases are increasingly important for surveillance, evidence appraisal, and quantitative risk assessment, yet their routine ...
BACKGROUND: Identifying communities disproportionately affected by hepatitis C infection is essential for targeted prevention and resource allocation....
BACKGROUND: Effective prevention of drowning and aquatic incidents requires timely and accurate surveillance supported by high-quality validated data....
SUMMARYAfrica's ongoing struggles with emerging epidemics and antimicrobial resistance (AMR) underscore the urgency of integrating pathogen genomics a...
In this paper, a dynamic epidemic model of botnet attack propagation in scale-free networks is introduced based on the epidemic model. The proposed at...
Dengue transmission in inland Southeast Asia shows strong seasonality and short-term surges that challenge timely public-health response. We assessed ...