Decomposing Vision-based LLM Predictions for Auto-Evaluation with GPT-4

arXiv:2403.05680v1 Announce Type: cross
Abstract: The volume of CT exams being done in the world has been rising every year, which has led to radiologist burn-out. Large Language Models (LLMs) have the potential to reduce their burden, but their adoption in the clinic depends on radiologist trust, and easy evaluation of generated content. Presently, many automated methods are available to evaluate the reports generated for chest radiographs, but such an approach is not available for CT presently. In this paper, …

abstract adoption arxiv auto cs.ai cs.cl cs.cv easy evaluation every exams generated gpt gpt-4 language language models large language large language models llm llms predictions radiologist reduce trust type vision world