Automated Complication Classification is a computational method that enables the systematic identification and categorization of post-implant complications by applying machine learning or rule-based systems to clinical, imaging, or sensor data, distinguishing it from general diagnostic approaches through its specificity to implant-related adverse events and its capacity for unsupervised or semi-supervised detection in longitudinal patient monitoring.