A pancreatic cystic lesion data processing method and system

Abstract

This invention relates to the field of medical data processing technology, and more particularly to a method and system for processing pancreatic cystic lesion data. When encoding multi-category variables, this invention directly injects clinical knowledge into the data features through a quantifiable, externally evidence-based risk progression matrix and hierarchical risk weights. This is equivalent to providing an artificial intelligence model with a learning guide, allowing it to learn from scratch, thereby accelerating convergence and improving prediction accuracy. Simultaneously, the encoding method provided in this embodiment has significantly different numerical characteristics; this difference can be more effectively captured by the model, especially when dealing with highly imbalanced or risk-differential categories, significantly improving the model's sensitivity to high-risk categories.

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