An interpretable AutoML-based prediction model for enteral nutrition intolerance in severe pulmonary tuberculosis patients and development of a clinical decisio... (opens in new tab)

ObjectiveThis study aims to construct an AutoML-based predictive model for enteral nutrition intolerance (ENI) in severe pulmonary tuberculosis (PTB) patients and develop a visualized clinical decision support system to inform personalized nutrition management.MethodsUsing a multicenter retrospective cohort design, clinical data from 645 severe PTB patients were analyzed. An Improved Dimension-wise Gaussian-mutated Chaotic Divine Religions Algorithm (IDRA) was proposed and integrated into the...