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Exploring the Potentials of Artificial Intelligence in Sepsis Management in the Intensive Care Unit

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AI models can predict sepsis earlier than traditional methods, enhancing patient outcomes and survival rates.
Machine learning techniques achieve AUROC scores between 0.8 and 0.99, demonstrating high accuracy in identifying sepsis.
Review of existing AI methodologies uncovers challenges like algorithmic bias and data fragmentation in current models.
Addressing the limitations of AI in sepsis management may pave the way for more effective and reliable clinical tools.

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Analysis reveals AI's potential to advance sepsis detection in ICUs, highlighting critical intervention opportunities.

Riahi et al. (2025) studied this question.

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