GPT-4愿景:聊天GPT的多模式演变以及在放射学中的潜在作用
Ramin Javan1, Theodore Kim1, Navid Mostaghni2
1Department of Radiology, George Washington University School of Medicine and Health Sciences, Washington, USA.
Cureus
|October 1, 2024
概括
大型多式联络模型GPT-4 Vision (GPT-4V) 显示了通过分析图像和帮助决策支持来增强放射学工作流程的潜力. 然而,目前的局限性需要在临床整合之前进一步开发.
科学领域:
- 人工智能的人工智能
- 多式联络AI 多式联络AI
- 放射学 放射学是一门学科.
背景情况:
- 大型语言模型 (LLM) 正在演变为大型多式模式模型 (LMM),如GPT-4视觉 (GPT-4V).
- 人工智能的进步有可能改善放射学工作流程和临床决策支持.
研究的目的:
- 探索GPT-4V在放射学中的潜在应用.
- 评估GPT-4V在各种与放射学相关的任务中的性能.
主要方法:
- 通过使用各种图像来源评估了GPT-4V的功能,包括网络图像,教学文件和草图.
- 任务包括科学图形分析,放射性图像报告,图像比较,手写解释,草图到代码和艺术表达.
主要成果:
- GPT-4V在图像分类,实体计数,图像比较和解读手写/草图方面表现出熟练.
- 在骨折检测,病变大小辨别,复杂图解解释和一致的放射性发现表征方面观察到局限性.
结论:
- GPT-4V对放射学有很大的希望,但在临床使用之前需要进一步培训以解决可靠性差距.
- 未来的代可以支持放射学任务,但人类的专业知识仍然对安全和道德实践至关重要.
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