Researchers build biomedical AI models trained on 3.4 million medical concepts from UMLS, comparing two approaches to make language models understand medical knowledge

Researchers created BERTUMLS and BioBERTUMLS — language models (AI systems that understand and generate text) trained on structured medical knowledge from UMLS Metathesaurus, a database of 3.4 million medical concepts and 34.2 million relationships. They tested two methods: embedding medical knowledge directly into the model during training, and using a knowledge graph (a map of how medical terms connect) that the AI consults when answering questions.