Latest AI and machine learning research in public health & policy for healthcare professionals.
Suicide poses a global health crisis with significant social and economic impact. Prevention may be possible if objective quantitative methods are developed to supplement the often inaccurate interview-based risk assessments. Our research goal is to develop a machine learning algorithm (MLA) to predict the presence of suicide ideation from resting state electroencephalography (EEG) data collected ...
In recent years, the United States has witnessed a significant surge in the popularity of vaping or e-cigarette use, leading to a notable rise in cases of e-cigarette and vaping use-associated lung injury (EVALI) that caused hospitalizations and fatalities during the EVALI outbreak in 2019, highlighting the urgency to comprehend vaping behaviors and develop effective strategies for cessation. Du...
OBJECTIVE: Social media-based public health research is crucial for epidemic surveillance, but most studies identify relevant corpora with keyword-mat...
Assessing heterogeneous treatment effects (HTEs) is an essential task in epidemiology. The recent integration of machine learning into causal inferenc...
COVID-19 is caused by the SARS-CoV-2 virus, which has produced variants and increasing concerns about a potential resurgence since the pandemic outbre...
Human Action Recognition (HAR) encompasses the task of monitoring human activities across various domains, including but not limited to medical, edu...
BACKGROUND: Previous studies have indicated that creatinine (Cr)-based glomerular filtration rate (GFR) estimating equations - including the new Chron...
Analysis of phylogenetic trees has become an essential tool in epidemiology. Likelihood-based methods fit models to phylogenies to draw inferences abo...
In order to clarify the transmission mechanism of the impact of mechanization on the occupational health of miners and to provide empirical evidence f...
Artificial intelligence (AI) holds the promise of addressing many of the numerous challenges healthcare faces, which include a growing burden of illne...
Artificial Intelligence (AI) applications have shown promise in the management of pandemics. In response to the global Monkeypox (Mpox) outbreak, the ...
The food security of China as a big agricultural country is attracting increasing attention. With the progress in the traditional Chinese medicine ind...
OBJECTIVES: In 2018, CMS established reimbursement for the first Medicare-covered artificial intelligence (AI)-enabled clinical software: CT fractiona...
Health and risk of disease are determined by exposure to the physical, socio-economic, and political environment and to this has been added exposure t...
BACKGROUND: Malaria remains one the leading communicable causes of death. Approximately half of the world's population is considered at risk of infect...
Foodborne illnesses, particularly those caused by Salmonella enterica with its extensive array of over 2600 serovars, present a significant public hea...
Disease ontologies facilitate the semantic organization and representation of domain-specific knowledge. In the case of prostate cancer (PCa), large v...
In Taiwan, the number of applications for inspecting imported food has grown annually and noncompliant products must be accurately detected in these b...
The current corpus of evidence-based information for chronic disease prevention and treatment is vast and growing rapidly. Behavior change theories ar...
The context of health care in Australia is shifting very rapidly; more chronic diseases, budgetary stress and the constant threat of the next pandemic...