Position: Open and Closed Large Language Models in Healthcare

Jiawei Xu, Ying Ding, Yi Bu

Keywords: Large Language Models, Healthcare, Open-source, Adaptability, Scientific Impact

Abstract:

This position paper provides an analysis of the evolving roles of open-source and closed-source large language models (LLMs) in healthcare, emphasizing their distinct contributions and the scientific community’s response to their development. Closed LLMs, such as GPT-4, have dominated high-performance applications, particularly in medical imaging and multimodal diagnostics, due to their advanced reasoning capabilities. Conversely, open LLMs, like Meta’s LLaMA, have gained popularity for their adaptability and cost-effectiveness, enabling researchers to fine-tune models for specific domains, such as mental health and patient communication.

Submission Number: 45