膀瘤识别和等级预测的人工智能诊断依赖于窄带成像囊镜
Yinchao Wang1, Hao Liang2, Yaozhong Zhang1
1Department of Urology, Qilu Hospital of Shandong University, Jinan 250012, Shandong, China.
iScience
|February 9, 2026
概括
一个人工智能系统有助于膀癌的诊断和通过囊镜进行分级. 这种人工智能辅助的NBI囊诊断系统 (AINCDS) 显示出高准确度,并提高泌尿科医生的性能,可能减少工作量.
科学领域:
- 泌尿器科 泌尿器科 泌尿器科 泌尿器科
- 人工智能的人工智能
- 医疗成像医学成像
背景情况:
- 通过囊泡镜进行早期膀癌症评估对于有效治疗至关重要.
- 准确的瘤分类对治疗计划具有临床意义.
- 现有的诊断方法可能在精度和泌尿科医生的工作量方面存在局限性.
研究的目的:
- 报告人工智能辅助的NBI囊诊断系统 (AINCDS) 的应用和性能.
- 评估AINCDS的诊断准确性,用于膀癌的识别和瘤等级的预测.
- 评估AINCDS对不同经验水平的泌尿科医生的诊断性能的影响.
主要方法:
- 开发人工智能辅助的NBI囊检查诊断系统 (AINCDS),包括特征提取,损伤细分和多任务分类的模块.
- 评估AINCDS在识别膀癌和使用囊泡镜数据预测瘤等级方面的表现.
- 对经验丰富的泌尿科医生进行AINCDS准确度的比较分析,并评估其对不那么经验丰富的泌尿科医生的表现的影响.
主要成果:
- 在确定膀癌时,AINCDS的准确度为0.919 (95% CI = 0.896到0.938).
- 该系统对预测瘤等级的准确性为0.764 (95% CI = 0.714到0.810).
- 来自AINCDS的协助改善了1-3年经验的泌尿科医生中的瘤等级预测准确度,从0.667到0.793.
结论:
- 在膀癌的诊断和分级方面,AINCDS表现出与经验丰富的泌尿科医生相比的能力.
- 该系统有可能提高诊断准确度,并减少泌尿科医生的工作量.
- AINCDS为改善膀癌评估和患者管理提供了一个有前途的工具.
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