人工智能在炎症性肠病内镜中的应用
Sabrina Gloria Giulia Testoni1,2, Guglielmo Albertini Petroni2, Maria Laura Annunziata2
1Unit of Gastroenterology and Digestive Endoscopy, Scientific Institute for Research, Hospitalization and Healthcare Policlinico San Donato, Vita-Salute San Raffaele University, San Donato Milanese, 20097 Milan, Italy.
人工智能 (AI) 通过分析内镜图像来帮助诊断炎症性肠病 (IBD). 人工智能在提高准确性,区分克罗恩病 (CD) 和性结肠炎 (UC) 和预测更好的患者护理结果方面表现有希望.
科学领域:
- 胃肠病学和肝病学
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 炎症性肠道疾病 (IBD),包括克罗恩病 (CD) 和性结肠炎 (UC),是慢性胃肠道疾病,患病率越来越高,病因复杂.
- 尽管治疗方面取得了进展,但仍然存在未得到满足的需求,特别是在准确评估粘膜愈合,内镜活动和发育不良方面,这些对预测患者的结果至关重要.
- 人工智能 (AI) 正在成为医学成像中的变革性工具,为IBD管理中客观和可重复的分析提供了潜在的解决方案.
研究的目的:
- 本综述旨在总结AI在IBD内镜中的应用方面的最新进展.
- 突出AI在提高IBD内镜评估诊断准确性和预后价值方面的潜力.
- 探索人工智能整合如何有助于开发IBD的精准医学方法.
主要方法:
- 对IBD内镜中AI应用的当前文献的审查,包括深度学习和模式识别技术.
- 分析AI在图像分类,病变细分和粘膜异常早期检测中的作用.
- 评估AI在区分IBD亚型,评估内镜活动和预测组织学结果方面的表现.
主要成果:
- 人工智能在特定场景中显示出区分性结肠炎 (UC) 和克罗恩病 (CD) 的潜力,并显著减少囊内镜检查时间.
- 人工智能工具可以改善内镜报告和评分中的观察者之间的和观察者内部的变异性.
- 初步的研究表明,人工智能能够预测组织学分数和检测肌肉发育不良,这对于风险分层至关重要.
结论:
- 在IBD内镜中的AI还处于早期阶段,但对提高我们对IBD复杂性和异质性的理解有显著的希望.
- 人工智能驱动的工具有潜力通过提供更准确和可重复的评估来改善患者护理和结果.
- 人工智能的整合预计将在促进炎症性肠道疾病的精准医学方面发挥关键作用.
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