对于炎症性肠病的内镜和超声波成像中的人工智能
Rareș Crăciun1,2, Andreea Livia Bumbu1,3, Vlad Andrei Ichim1,3
1Department of Internal Medicine, "Iuliu Hațieganu" University of Medicine and Pharmacy, 8 Victor Babes Street, 400012 Cluj-Napoca, Romania.
人工智能 (AI) 正在彻底改变炎症性肠病 (IBD) 成像,提高病变检测和内镜和超声波中的疾病评分. 人工智能集成有望提高诊断准确性和患者的治疗结果,但实施方面仍然存在挑战.
科学领域:
- 医疗成像医学成像
- 人工智能的人工智能
- 胃肠病学 胃肠病学
背景情况:
- 炎症性肠病 (IBD) 的成像,特别是内镜和超声波,面临着诸如观察者间变异性和主观性等挑战.
- 人工智能 (AI) 为克服IBD诊断中的这些局限性提供了重大机会.
研究的目的:
- 对IBD成像模式的AI整合的最新进展进行审查.
- 突出AI在改善IBD管理中的诊断准确性,治疗策略和患者结果方面的潜力.
主要方法:
- 对人工智能在IBD中的内镜,超声波和视频囊内镜应用的最新发展进行了审查.
- 分析AI在病变检测,疾病活动评分和临床决策支持方面的作用.
主要成果:
- 人工智能,特别是深层卷积神经网络,在检测粘膜异常和在内镜中分级IBD严重程度方面表现出很高的准确性.
- 人工智能辅助结肠镜可以提高腺瘤检测率和程序质量.
- 肠道超声波中的AI自动化测量并有助于区分炎症和纤维性狭窄.
- 人工智能通过减少解释时间和改善微妙病变检测来增强视频囊内镜.
结论:
- 在IBD成像模式中整合AI为提高诊断准确性和标准化评估提供了巨大的潜力.
- 解决数据质量,标准化,可解释性和临床医生接受等实施挑战对于在IBD护理中广泛采用AI至关重要.
- 人工智能驱动的进步有望优化治疗策略并改善患者在炎症性肠病管理中的结果.
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