Urban public health resilience has become a critical focus in the transition to high-quality development, especially in addressing increasing public health challenges. This study explores the role of artificial intelligence (AI) technology in enhanci...
BACKGROUND: Machine learning is pivotal for predicting Peripherally Inserted Central Catheter-related venous thrombosis (PICC-RVT) risk, facilitating early diagnosis and proactive treatment. Existing models often assess PICC-RVT risk as static and di...
Life course immunisation looks at the broad value of vaccination across multiple generations, calling for more data power, collaboration, and multi-disciplinary work. Rapid strides in artificial intelligence, such as machine learning and natural lang...
There is a critical need for community engagement in the process of adopting artificial intelligence (AI) technologies in public health. Public health practitioners and researchers have historically innovated in areas like vaccination and sanitation ...
The integration of artificial intelligence (AI) into health communication systems has introduced a transformative approach to public health management, particularly during public health emergencies, capable of reaching billions through familiar digit...
PURPOSE: The objective of this study is to investigate the predictive ability of machine learning models for imbalanced outcomes from national survey data without the use of sampling weights.
Explore deep learning applications in predictive analytics for public health data, identify challenges and trends, and then understand the current landscape. A systematic literature review was conducted in June 2023 to search articles on public hea...
Integrating prior epidemiological knowledge embedded within mechanistic models with the data-mining capabilities of artificial intelligence (AI) offers transformative potential for epidemiological modeling. While the fusion of AI and traditional mech...
The emergence of artificial intelligence (AI) in drug discovery represents a transformative development in addressing neglected diseases, particularly in the context of the developing world. Neglected diseases, often overlooked by traditional pharmac...
BACKGROUND: Sentiment analysis is one of the most widely used methods for mining and examining text. Social media researchers need guidance on choosing between manual and automated sentiment analysis methods.