ChatGPT, Bard, and Large Language Models for Biomedical Research: Opportunities and Pitfalls

Abstract

Large Language Models (LLMs) such as ChatGPT and Bard have emerged as groundbreaking interactive chatbots, capturing significant attention and transforming the biomedical research landscape. These powerful tools offer immense potential for advancing scientific inquiry, but they also present challenges and pitfalls. Leveraging large language models, researchers can streamline literature reviews, summarize complex findings, and even generate novel hypotheses, enabling the exploration of uncharted scientific territories. However, the inherent risk of misinformation and misleading interpretations underscores the critical importance of rigorous validation and verification processes. This article provides a comprehensive overview of the current landscape and delves into the opportunities and pitfalls associated with employing LLMs in biomedical research. Furthermore, it sheds light on strategies to enhance the utility of LLMs in biomedical research, offering recommendations to ensure their responsible and effective implementation in this domain. The findings presented in this article contribute to the advancement of biomedical engineering by harnessing the potential of LLMs while addressing their limitations.

Keywords: Bard; Biomedical research; ChatGPT; Large language models; Natural language processing.