系统性疾病患者内牙治疗中的临床决策准确性:使用不同人工智能模型进行比较分析
Ayşegül Eroğlu1, İpek Eraslan Akyüz1, Emre Yılmaz2
1Department of Endodontics, Faculty of Dentistry, Erciyes University, 38039, Melikgazi, Kayseri, Türkiye.
Odontology
|February 11, 2026
概括
四个人工智能 (AI) 模型在医疗损害患者的内牙治疗计划中显示出类似的准确性. 虽然人工智能可以支持决策,但它不应该取代牙周内科的专家临床判断.
科学领域:
- 牙科 牙科是指牙科的专业.
- 人工智能的人工智能
- 医疗信息学 医疗信息学
背景情况:
- 系统性疾病使内牙治疗计划复杂化.
- 人工智能 (AI) 在复杂的医疗病例中提供潜在的决策支持.
- 在牙科专业领域 (如内科医生) 评估人工智能的准确性至关重要.
研究的目的:
- 为了比较四个AI模型 (ChatGPT-5.1,Gemini 2.5 Pro,Gemini 2.5 Flash,ChatGPT-3.5) 在内治疗规划中的临床决策准确度.
- 在涉及全身疾病患者的场景中评估AI性能.
- 为了确定任何人工智能模型是否在这种临床环境中始终优于其他模型.
主要方法:
- 一项横截面的教育研究使用了40个标准化的内牙科临床场景,用于患有全身性疾病的患者.
- 四个人工智能模型在孤立的环境中使用相同的提示进行了查询.
- 人工智能反应由两个校准的内牙科医生使用四个领域的10分评分系统来评估.
主要成果:
- 在AI模型中,在整体临床决策准确性或特定领域得分方面没有发现统计学上显著的差异.
- 虽然分类分析显示了高准确度响应的总体差异,但对对比并没有显著.
- 所有模型都表现出与专家定义的最佳决策相似的接近性,而Gemini 2.5 Flash显示出更大的可变性.
结论:
- 目前的人工智能模型在医学上受损患者的内牙治疗计划中表现相似.
- 在评估的场景中,没有单一的人工智能模型在评估的场景中始终超过其他模型.
- 人工智能可以作为一种支持工具,但不应该取代牙周内科的专业临床判断.
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