在临床诊断实验室中,人工智能辅助解释ANA HEp-2 IIF测定模式的手册与人工智能辅助解释的比较
Jonas Schmidt1, Sarina Weiß1, Frithjof Blessing2
1Institute for Laboratory Medicine, Singen, Germany.
Clinica chimica acta; international journal of clinical chemistry
|February 2, 2026
概括
人工智能 (AI) 软件在通过间接免疫光 (IIF) 来分类反核抗体 (ANA) 模式方面,表现与人类专家相美. 这种人工智能辅助的图像分析有助于ANA测试的诊断工作流程,并减少了主观性.
科学领域:
- 免疫学 免疫学 免疫学
- 医学诊断 医学诊断 医学诊断
- 人工智能的人工智能
背景情况:
- 通过HEp-2细胞的间接免疫光 (IIF) 检测抗核抗体 (ANA) 对于诊断系统性自身免疫性风湿性疾病至关重要.
- 目前的解释依赖于专家的阅读,这可能是主观的.
研究的目的:
- 为了比较新型人工智能辅助模式识别系统的ANA分类与专家人类解释的性能.
- 评估AI在自动化ANA IIF图像分析中的实用性.
主要方法:
- 分析了2671个血清样本,使用akironNeo自动化解释系统对ANA标位和模式进行分析.
- 基于AI的ANA检测与两个经验丰富的免疫学家根据ICAP指南进行的独立分类进行了比较.
主要成果:
- 人工智能和人类专家之间在积极/消极的ANA分类和模式识别 (介相,转相,细胞质) 之间观察到良好的一致性 (κ > 0.60).
- 对正负分化的 κ 值在0.584到0.760.0之间.
- 在阳性样本 (滴值≥1:320) 中,图案识别的 κ值在0.560到0.736.6之间.
结论:
- 基于人工智能的软件在ANA图像分析中与人类观察员的表现类似.
- 人工智能辅助的ANA图像分析可以简化ANAIIF试验的诊断工作流程.
- 人工智能有可能减少ANA图像分类中的主观性.
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