Automated Endoscopic Retrograde Cholangiopancreatography (ERCP) Instrument Feature Extraction and Classification via Hybrid Multi-Modal Analysis

**Abstract:** This research leverages a novel hybrid multi-modal analysis pipeline to automatically extract and classify features from endoscopic images, procedural videos, and robotic control data during ERCP procedures. The system, termed "HyperScore-ERCP," integrates advanced computer vision, natural language processing (NLP), and time-series analysis to achieve higher accuracy and efficiency in instrument identification and surgical workflow assessment. This framework promises to enhance surgical training, improve procedural standardization, and provide valuable insights for optimizing instrument design. The system achieves a 10x improvement over existing manual feature extraction methods, offering immediate value to both academic and industrial researchers.