<ul><li>Sepsis prediction remains challenging due to non-specific symptoms and complex pathophysiology, despite medical advancements.</li><li>The SXI++ LNM algorithm, a machine learning scoring system, aims to refine sepsis prediction by utilizing multiple algorithms and deep neural networks.</li><li>A study was conducted to evaluate the predictive performance of the SXI++ LNM for sepsis prediction, using a deep neural network trained and tested with different dataset distributions.</li><li>The SXI++ LNM outperformed the state of the art in three use cases, achieving high AUC, precision, and accuracy, demonstrating reliability in sepsis prediction.</li></ul>

Development and Validation of SXI++ LNM Algorithm for Sepsis Prediction

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