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Falls are a leading cause of injury in older adults, making risk prediction a clinical priority. While many machine learning (ML) models exist, they typically provide a static assessment, predicting risk for a single, fixed timeframe. This approach overlooks how the clinical drivers of risk evolve over time, failing to distinguish between acute factors that signal an imminent fall and chronic conditions that confer long-term v...
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