Medication Recommendation

Medication recommendation systems aim to improve healthcare by providing personalized and evidence-based drug suggestions. Current research focuses on leveraging electronic health records (EHRs) and incorporating diverse data sources, such as clinical notes and molecular structures, using advanced machine learning models like graph neural networks, transformers, and large language models (LLMs). These models are being refined to address challenges like data sparsity, handling complex temporal relationships in patient histories, and ensuring fairness and safety in recommendations. Ultimately, these advancements hold significant potential to enhance clinical decision-making, improve patient outcomes, and optimize treatment efficacy.