Predicting Postoperative Complications in Laparoscopic General Surgery Using Machine and Deep Learning: A Classification Approach (Under Review)
This research paper develops and evaluates machine learning and deep learning models to predict six critical postoperative complications: Cardiac Arrest, Myocardial Infarction, Pulmonary Embolism, Reintubation, Pneumonia, and Failure to Wean from Ventilator.
A Benchmark for Graph-Based Dynamic Recommendation Systems
This research paper aims to provide a comprehensive benchmarking framework for evaluating the performance of graph-based dynamic recommendation systems. Key algorithms covered SAGE (GraphSAGE), GAT (Graph Attention Networks), GIN (Graph Isomorphism Networks), and additional state of the art Graph Neural Network architectures.