Position: Open and Closed Large Language Models in Healthcare

• URL: http://arxiv.org/abs/2501.09906v1
• Date: Fri, 17 Jan 2025 01:36:52 GMT
• Title: Position: Open and Closed Large Language Models in Healthcare
• Authors: Jiawei Xu, Ying Ding, Yi Bu,
• Abstract summary: This position paper analyzes the evolving roles of open-source and closed-source large language models (LLMs) in healthcare. It emphasizes their distinct contributions and the scientific community's response to their development.
• Score: 7.298307551137158
• License:
• 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.

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