Biomedical System

Biomedical systems research focuses on developing computational models to understand and predict complex biological processes, aiming to improve diagnostics and treatments. Current efforts leverage machine learning, particularly deep learning and agent-based modeling, often integrated with knowledge graphs and symbolic reasoning, to analyze diverse biomedical data (e.g., biosignals, medical images, electronic health records). These approaches are applied to various challenges, including disease prediction, drug discovery, and personalized medicine, with a strong emphasis on ensuring data privacy and addressing issues like data imbalance. The ultimate goal is to create more accurate, interpretable, and robust models for advancing healthcare.