# Assessing the feasibility of large language models to identify top research priorities in enhanced external counterpulsation

## TL;DR

This paper explores how large language models can help identify key research priorities in enhanced external counterpulsation, a cardiovascular treatment.

## Contribution

The study introduces the use of large language models to prioritize research areas in EECP, validated by expert evaluation.

## Key findings

- Large language models generated research priorities across five EECP domains.
- Experts gave high scores to the generated priorities based on relevance and originality.
- The results suggest AI can effectively support research prioritization in EECP.

## Abstract

Enhanced External Counterpulsation (EECP), as a non-invasive, cost-effective, and efficient adjunctive circulatory technique, has been widely applied in in the cardiovascular field. Numerous studies and clinical observations have confirmed the obvious advantages of EECP in promoting blood flow perfusion to vital organs such as the heart, brain, and kidneys. However, many potential mechanisms of EECP remain insufficiently validated, necessitating researchers to dedicate substantial time and effort to in-depth investigations. In this work, large language models (such as ChatGPT and Ernie Bot) were used to identify top research priorities in five key topics in the field of EECP: mechanisms, device improvements, cardiovascular applications, neurological applications, and other applications. After generating specific research priorities in each domain through language models, a panel of nine experienced EECP experts was invited to independently evaluate and score them based on four parameters: relevance, originality, clarity, and specificity. Notably, high average and median scores for these evaluation parameters were obtained, indicating a strong endorsement from experts in the EECP field. This study preliminarily suggests that large language models like ChatGPT and Ernie Bot could serve as powerful tools for identifying and prioritizing research priorities in the EECP domain.