Poster
in
Workshop: GenAI for Health: Potential, Trust and Policy Compliance
Position: Open and Closed Large Language Models in Healthcare
Jiawei Xu · Ying Ding · Yi Bu
Keywords: [ Large Language Models ] [ Healthcare ] [ Scientific Impact ] [ Open-source ] [ Adaptability ]
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.