Opportunities and Challenges for ChatGPT and Large Language Models in Biomedicine and Health

Area of Science:

• Biomedical informatics
• Artificial intelligence in healthcare

Background:

• Large language models (LLMs), exemplified by ChatGPT, exhibit advanced text generation capabilities, prompting exploration of their use in biomedicine and health.
• The integration of LLMs into healthcare necessitates an understanding of their potential impact on tasks like information retrieval, question answering, and medical education.

Approach:

• An extensive literature survey was conducted to evaluate the applications of LLMs in various biomedical and health domains.
• The study assesses whether LLMs can revolutionize these fields or if domain-specific complexities pose significant challenges.

Key Points:

• LLMs have demonstrated significant advances in text generation tasks, outperforming previous state-of-the-art methods.
• Progress in other LLM applications within biomedicine has been modest, indicating areas for future development.
• Despite current limitations, LLMs hold considerable potential for accelerating biomedical discovery and enhancing health outcomes.

Conclusions:

• LLMs have not yet revolutionized the biomedical field but show great promise for future advancements.
• The application of LLMs in healthcare presents risks, including the generation of fabricated information and concerns regarding patient data privacy and security.
• This survey provides a comprehensive overview for researchers and practitioners on the opportunities and challenges of utilizing LLMs in biomedicine and health.