Honglin Shang

Early Warning of Intraoperative Adverse Events via Transformer-Driven Multi-Label Learning

Early warning of intraoperative adverse events plays a vital role in reducing surgical risk and improving patient safety. While deep learning has shown promise in predicting the single adverse event, several key challenges remain: overlooking adverse event dependencies, underutilizing heterogeneous