Comment by Quantifying Evidence for Competing Biomedical Hypotheses using Large Language Models and Bayesian Analysis

Here, we introduce KM-GPT-DCH, an algorithm that combines co-occurrence methods with large language models (LLMs) to develop a transparent and reproducible literature-based algorithm to compare controversial hypotheses using a structured scoring approach with Bayesian methods to estimate confidence.