English

Position: Open and Closed Large Language Models in Healthcare

Computers and Society 2025-01-20 v1

Abstract

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.

Keywords

Cite

@article{arxiv.2501.09906,
  title  = {Position: Open and Closed Large Language Models in Healthcare},
  author = {Jiawei Xu and Ying Ding and Yi Bu},
  journal= {arXiv preprint arXiv:2501.09906},
  year   = {2025}
}

Comments

Accepted by GenAI for Health Workshop @ NeurIPS 2024, Vancouver