Leveraging Federated Learning for Predicting Kidney Graft Survival Using OPTN Dataset
The paper presents a federated learning approach for kidney graft survival prediction using the OPTN dataset. The work emphasizes privacy-preserving collaborative learning without sharing patient-level data.
Enhancing Kidney Transplant Compatibility Outcomes through Graph Attention-Based Learning
This research proposes a Graph Attention Network-based framework for modelling donor–recipient relationships. The objective is to improve compatibility assessment by learning complex interactions among transplant variables.
Recognizing Cardiovascular Risk Patterns using Ensemble Learning Techniques
This work investigates cardiovascular risk prediction using ensemble machine learning techniques. It evaluates multiple ensemble models to improve prediction accuracy and support early clinical decision-making.