The American journal of medicine
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This study aimed to compare the demographic features and socioeconomic status of patients who underwent coronary artery calcium screening to that of their local population. ⋯ The disproportionate distribution of coronary artery calcium screening favoring educated, affluent, White English speakers indicates that higher-income and healthcare personnel are more likely to receive testing. Disparities in coronary artery calcium testing, especially in minorities and non-English speaking individuals, should be further explored.
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Machine learning algorithms are essential for predicting severe outcomes during public health crises like COVID-19. However, the dynamic nature of diseases requires continual evaluation and updating of these algorithms. This study aims to compare three update strategies for predicting severe COVID-19 outcomes postdiagnosis: "naive" (a single initial model), "frequent" (periodic retraining), and "context-driven" (retraining informed by clinical insights). The goal is to determine the most effective timing and approach for adapting algorithms to evolving disease dynamics and emerging data. ⋯ A context-driven approach, guided by clinical insights, can enhance predictive performance and offer cost-effective solutions for dynamic public health challenges. These findings have significant implications for efficiently managing healthcare resources during evolving disease outbreaks.