Standard Sepsis

Standard sepsis, a life-threatening condition characterized by organ dysfunction due to infection, is a major focus of research aimed at improving early diagnosis and treatment. Current efforts utilize machine learning, including neural networks (e.g., recurrent, convolutional, and transformer models), and other advanced statistical methods (e.g., Bayesian networks) to analyze diverse data sources, such as physiological time series, laboratory biomarkers, and clinical notes, to predict sepsis onset, severity, and mortality risk. These advancements hold significant promise for improving patient outcomes through earlier interventions and personalized treatment strategies, ultimately reducing sepsis-related morbidity and mortality.