This systematic review examines the predictive performance, methodological quality, and clinical applicability of machine learning models developed to predict 30-day hospital readmission following acute exacerbation of chronic obstructive pulmonary disease (COPD). By synthesizing evidence from published studies, the review aims to evaluate model discrimination, calibration, validation strategies, predictor selection, and reporting quality to identify reliable prediction models that can support risk stratification, targeted interventions, and the reduction of preventable hospital readmissions.Click-Here-(Apply Form).com__________________________________
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