Publications by authors named "Saikrishna Pannaga Srikar Gundreddy"

Background: 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).

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