Rey Jean-Francois
Institut Arnaut Tzanck Gastrointestinal Unt, Saint Laurent du Var, France.
Clin Endosc. 2024 May;57(3):302-308. doi: 10.5946/ce.2023.230. Epub 2024 Mar 8.
With incessant advances in information technology and its implications in all domains of our lives, artificial intelligence (AI) has emerged as a requirement for improved machine performance. This brings forth the query of how this can benefit endoscopists and improve both diagnostic and therapeutic endoscopy in each part of the gastrointestinal tract. Additionally, it also raises the question of the recent benefits and clinical usefulness of this new technology in daily endoscopic practice. There are two main categories of AI systems: computer-assisted detection (CADe) for lesion detection and computer-assisted diagnosis (CADx) for optical biopsy and lesion characterization. Quality assurance is the next step in the complete monitoring of high-quality colonoscopies. In all cases, computer-aided endoscopy is used, as the overall results rely on the physician. Video capsule endoscopy is a unique example in which a computer operates a device, stores multiple images, and performs an accurate diagnosis. While there are many expectations, we need to standardize and assess various software packages. It is important for healthcare providers to support this new development and make its use an obligation in daily clinical practice. In summary, AI represents a breakthrough in digestive endoscopy. Screening for gastric and colonic cancer detection should be improved, particularly outside expert centers. Prospective and multicenter trials are mandatory before introducing new software into clinical practice.
随着信息技术的不断进步及其在我们生活各个领域的影响,人工智能(AI)已成为提高机器性能的一项要求。这引发了一个问题,即它如何能使内镜医师受益,并改善胃肠道各部位的诊断性和治疗性内镜检查。此外,它还引发了关于这项新技术在日常内镜实践中的近期益处和临床实用性的问题。人工智能系统主要有两大类:用于病变检测的计算机辅助检测(CADe)和用于光学活检及病变特征描述的计算机辅助诊断(CADx)。质量保证是全面监测高质量结肠镜检查的下一步。在所有情况下,都会使用计算机辅助内镜检查,因为总体结果依赖于医生。视频胶囊内镜是一个独特的例子,其中计算机操作设备、存储多个图像并进行准确诊断。尽管有很多期望,但我们需要对各种软件包进行标准化和评估。医疗保健提供者支持这一新发展并使其在日常临床实践中成为一项义务非常重要。总之,人工智能代表了消化内镜领域的一项突破。应改进胃癌和结肠癌检测的筛查,尤其是在专家中心以外的地方。在将新软件引入临床实践之前,必须进行前瞻性多中心试验。