Position: Open and Closed Large Language Models in Healthcare
Not on the map. Why?
Abstract (arXiv)
This position paper analyzes 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. Due to their advanced reasoning capabilities, closed LLMs, such as GPT-4, have dominated high-performance applications, particularly in medical imaging and multimodal diagnostics. 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.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). First posted on arXiv 17 Jan 2025.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2025: 1.
1 paper.