Uchikov Petar, Khalid Usman, Vankov Nikola, Kraeva Maria, Kraev Krasimir, Hristov Bozhidar, Sandeva Milena, Dragusheva Snezhanka, Chakarov Dzhevdet, Petrov Petko, Dobreva-Yatseva Bistra, Novakov Ivan
Department of Special Surgery, Faculty of Medicine, Medical University of Plovdiv, 4000 Plovdiv, Bulgaria.
Faculty of Medicine, Medical University of Plovdiv, 4000 Plovdiv, Bulgaria.
Diagnostics (Basel). 2024 May 13;14(10):1004. doi: 10.3390/diagnostics14101004.
This review aims to delve into the role of artificial intelligence in medicine. Ulcerative colitis (UC) is a chronic, inflammatory bowel disease (IBD) characterized by superficial mucosal inflammation, rectal bleeding, diarrhoea and abdominal pain. By identifying the challenges inherent in UC diagnosis, we seek to highlight the potential impact of artificial intelligence on enhancing both diagnosis and treatment methodologies for this condition.
A targeted, non-systematic review of literature relating to ulcerative colitis was undertaken. The PubMed and Scopus databases were searched to categorize a well-rounded understanding of the field of artificial intelligence and its developing role in the diagnosis and treatment of ulcerative colitis. Articles that were thought to be relevant were included. This paper only included articles published in English.
Artificial intelligence (AI) refers to computer algorithms capable of learning, problem solving and decision-making. Throughout our review, we highlighted the role and importance of artificial intelligence in modern medicine, emphasizing its role in diagnosis through AI-assisted endoscopies and histology analysis and its enhancements in the treatment of ulcerative colitis. Despite these advances, AI is still hindered due to its current lack of adaptability to real-world scenarios and its difficulty in widespread data availability, which hinders the growth of AI-led data analysis.
When considering the potential of artificial intelligence, its ability to enhance patient care from a diagnostic and therapeutic perspective shows signs of promise. For the true utilization of artificial intelligence, some roadblocks must be addressed. The datasets available to AI may not truly reflect the real-world, which would prevent its impact in all clinical scenarios when dealing with a spectrum of patients with different backgrounds and presenting factors. Considering this, the shift in medical diagnostics and therapeutics is coinciding with evolving technology. With a continuous advancement in artificial intelligence programming and a perpetual surge in patient datasets, these networks can be further enhanced and supplemented with a greater cohort, enabling better outcomes and prediction models for the future of modern medicine.
本综述旨在深入探讨人工智能在医学中的作用。溃疡性结肠炎（UC）是一种慢性炎症性肠病（IBD），其特征为浅表性黏膜炎症、直肠出血、腹泻和腹痛。通过识别UC诊断中固有的挑战，我们试图突出人工智能对改善该疾病诊断和治疗方法的潜在影响。
对与溃疡性结肠炎相关的文献进行了有针对性的非系统性综述。检索了PubMed和Scopus数据库，以全面了解人工智能领域及其在溃疡性结肠炎诊断和治疗中的发展作用。纳入了被认为相关的文章。本文仅包括以英文发表的文章。
人工智能（AI）是指能够学习、解决问题和进行决策的计算机算法。在我们的综述中，我们强调了人工智能在现代医学中的作用和重要性，重点介绍了其在人工智能辅助内镜检查和组织学分析诊断中的作用以及在溃疡性结肠炎治疗方面的改进。尽管取得了这些进展，但由于目前人工智能缺乏对现实世界场景的适应性以及难以获得广泛的数据，其发展仍然受到阻碍，这也阻碍了以人工智能为主导的数据分析的发展。
考虑到人工智能的潜力，其从诊断和治疗角度改善患者护理的能力显示出有希望的迹象。为了真正利用人工智能，必须解决一些障碍。人工智能可用的数据集可能无法真实反映现实世界，这将阻碍其在处理具有不同背景和呈现因素的各类患者时在所有临床场景中的影响。考虑到这一点，医学诊断和治疗的转变与技术的不断发展相契合。随着人工智能编程的不断进步以及患者数据集的持续增加，这些网络可以进一步得到增强，并通过更多的队列进行补充，从而为现代医学的未来带来更好的结果和预测模型。
