人工智能辅助的内镜超声诊断食道亚皮质病变的诊断
Ai-Meng Zhang1, Dai-Min Jiang2, Shu-Peng Wang1
1Department of Gastroenterology, Shengjing Hospital of China Medical University, No. 36, Sanhao Street, Shenyang, 110004, Liaoning Province, China.
Surgical endoscopy
|May 7, 2025
概括
用于内镜超声波 (EUS) 的人工智能 (AI) 模型在识别食道亚皮质病变 (SELs) 的起源层方面表现有前途. 这种EUS-AI工具可以显著提高诊断准确度,特别是对于经验较少的内镜师来说.
科学领域:
- 胃肠病学 胃肠病学
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 内镜超声波 (EUS) 对于确定食道亚皮质病变 (SEL) 的原始层至关重要.
- 对于SEL,EUS的诊断准确性高度依赖于内镜师的专业知识.
- 需要客观的工具来帮助SEL起源层的识别.
研究的目的:
- 开发和评估一种人工智能 (AI) 模型,使用EUS图像识别食道SELs的原始层.
- 与人类内镜师相比,评估人工智能模型的有效性.
主要方法:
- 使用YOLOv8s-seg和MobileNetv2架构开发了一个AI模型.
- 该模型在1445例食道SEL病例上接受了训练.
- 一组测试被两个高级和两个初级内镜师独立诊断,以进行比较.
主要成果:
- 人工智能模型的精度为92.2%,回忆率为73.6%,F1得分为81.9%.
- 原始层识别的整体准确率为55.2%,特定层的F1分数从47.1%到66.1%不等.
- 人工智能系统在分化层的准确性与高级内镜师相美,优于初级内镜师.
结论:
- 开发的EUS-AI模型显示了诊断食道SEL及其起源层的巨大潜力.
- EUS-AI可以作为一个有价值的工具来增强内镜师的诊断能力,特别是那些经验较少的人.
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