深度搜索TM和眼排水障碍:大肆宣传,还是比ChatGPTTM表现更好?
1Govindram Seksaria Institute of Dacryology, L.V. Prasad Eye Institute, Hyderabad, India.
Orbit (Amsterdam, Netherlands)
|May 8, 2025
概括
在解决眼排水障碍方面,DeepSeek和ChatGPT的表现相似. 这两种AI模型都显示出医疗应用的潜力,需要专门的培训才能获得最佳使用.
科学领域:
- 眼科医生 眼科 眼科
- 人工智能的人工智能
- 医疗信息学 医疗信息学
背景情况:
- 大型语言模型 (LLM) 越来越多地被用于医疗领域.
- 在专业医疗环境中评估LLM绩效对于采用至关重要.
- 眼排水障碍带来了复杂的诊断和管理挑战.
研究的目的:
- 评估DeepSeek LLM在眼排水障碍方面的表现.
- 为了将DeepSeek与ChatGPT在这个医疗子专业中进行对比.
- 为了评估AI聊天机器人随着时间的推移而得到的改进.
主要方法:
- 关于眼排水障碍的25个提示被用于查询DeepSeek和ChatGPT (2025年2月版本).
- 三位眼外科医生分析了答案的准确性,特异性和事实正确性.
- 使用ChatGPT的2023版本进行比较,以评估改进.
主要成果:
- 深度搜索和聊天GPT显示了类似的响应准确度 (分别是60%和56%.
- 模型之间没有观察到响应速度的显著差异.
- 与2023年版本相比,ChatGPT-2025在特定性和准确性方面取得了改进.
结论:
- 对于眼排水障碍的信息,DeepSeek与ChatGPT相当.
- 这两种AI模型都有优势,可以互补.
- 对于医疗子专业的AI模型,需要专门的培训.
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