Latest AI and machine learning research in public health & policy for healthcare professionals.
Adolescent use of alcohol, nicotine, and marijuana remains a major public health concern in the United States. Early identification of youth at elevated risk is critical for prevention before use begins or escalates. We developed and evaluated a longitudinal machine learning framework to predict alcohol, nicotine, and marijuana use at the next observed assessment wave. Data came from the Adolescen...
Introduction: Climate change disproportionately affects disadvantaged communities, yet construction workforce education rarely addresses interconnected pathways linking energy efficiency, nature exposure, and public health. Green-blue infrastructure delivers co-optimized benefits: reducing building energy consumption 15-30% while decreasing heat-related mortality by approximately 3.9% per degree C...
Background Timely assessment, classification, and escalation of public health events are essential for effective outbreak response, yet decision-makin...
Conventional mosquito surveillance typically relies on contemporaneous data, making it challenging to anticipate future vector surges. To support proa...
Public microbial genomes encode an immense record of biological diversity, evolution and molecular function, but much of this information remains diff...
Images acquired in surveillance environments often suffer from conditions such as low resolution, variations in pose, irregular illumination, and occl...
Background Early outbreak detection often depends on complex, data-intensive models that have limited operational use in sparse surveillance settings....
Abstract Objective Wrist-worn accelerometers are common in large-scale epidemiological studies, but their ability to measure sedentary behaviour in fr...
Background: Heart failure (HF) and chronic obstructive pulmonary disease (COPD) are among the leading causes of morbidity and mortality globally, with...
BackgroundGaps in care (GIC) among patients with congenital heart disease (CHD) are associated with adverse outcomes, yet the specific social and heal...
Outbreak transmission reconstruction treats epidemiological timing and transmission labels as deterministic ground truth; neither has been systematica...
Cancer registries enable cancer surveillance at the population level. These registries require significant human-time to read through many different p...
Timely intensive care dictates survival, yet emergency infrastructure remains unevenly distributed across Sri Lanka. While pre-hospital services have ...
Text-to-image person re-identification (TIPR) retrieves target persons using natural language descriptions. However, existing methods largely overlook...
The unprecedented growth of computer vision applications, such as surveillance systems and social media, raises security and visual privacy concerns, ...
Video Intelligence Surveillance (VIDINT) on over-the-shoulder footage is a proposed vector for monitoring human-computer interaction patterns without ...
Generative AI tools such as ChatGPT are increasingly used by the public to seek guidance on diet and physical activity for type 2 diabetes (T2D) preve...
ObjectiveTo evaluate the associations of short-term environmental exposures with subjective cognitive difficulties and attention-related outcomes and ...
Short-form video platforms increasingly shape how young audiences encounter health information. Generative artificial intelligence can produce standar...
The Covid-19 outbreak has adversely influenced university students across the world both physically and psychologically. The psychological struggle fa...