Biomedical Hypothesis

Biomedical hypothesis generation leverages artificial intelligence, particularly large language models (LLMs), to accelerate scientific discovery by identifying novel connections within the vast biomedical literature. Current research focuses on improving the accuracy and explainability of LLM-generated hypotheses, often employing retrieval-augmented generation (RAG) techniques and novel evaluation metrics that consider both the novelty and potential impact of the proposed hypotheses. This approach promises to significantly enhance the efficiency of biomedical research by automating hypothesis formulation, potentially leading to faster identification of new drug targets and improved understanding of disease mechanisms.