Jack Freeman

This paper introduces KM-GPT-DCH, a method using LLMs and Bayesian analysis to evaluate and compare biomedical hypotheses by analyzing scientific literature.

SKiM-GPT evaluates biomedical hypotheses by combining literature-based discovery with large language models to assess hypothesis validity using retrieved PubMed abstracts.

This study identifies significant reprogramming of nucleotide metabolism in classically activated macrophages, revealing key regulatory mechanisms and functional consequences.