Enhancing ICU Mortality Prediction through Hybrid-Optimized Recurrent Neural Networks

Sam M. K.

Enhancing ICU Mortality Prediction through Hybrid-Optimized Recurrent Neural Networks

Sam M. K.
Volume 7

Abstract

Accurate prediction of mortality rates among Intensive Care Unit (ICU) patients is a critical challenge in modern clinical medicine, as timely risk stratification enables physicians to prioritize interventions, allocate limited resources effectively, and improve patient survival outcomes. Despite significant advances in machine learning-based prognostic models, existing approaches often suffer from limited generalization, sensitivity to missing clinical data, and insufficient exploitation of temporal dependencies inherent in physiological time-series records.

Keywords

References

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