在现代妇科中使用人工智能的机遇

Q3 Medicine
Sh. L. Shailieva, D. K. Mamchueva, A. P. Vishnevskaya, Kh. Sh. Dzhalaeva, E. G. Ramazanova, Y. R. Kokaeva, Z. M. Eloeva, D. R. Aisanova, A. S. Vinogradova, R. R. Tuko, A. V. Sineva, L. A. Valiullina, A. A. Kutseva
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引用次数: 0

摘要

引言人工智能(AI)是一种模拟人脑数据处理、智力行为和批判性思维的技术。先进的人工智能模型可以通过加快流程、提高准确性和效率来改善患者管理,同时降低人力资源成本。与其他专科相比,人工智能在妇科领域的应用仍处于起步阶段。重要的是要明白,现有的临床成像方法有一定的局限性,即临床医生的工作量和不同医生对数据的解释存在差异。反过来,人工智能有可能克服这些局限性,同时提高诊断的准确性。目的:构建并分析目前已发表的关于人工智能在妇科中应用的数据。在电子数据库 PubMed、eLibrary 和 Google Scholar 中搜索原始资料。检索查询包括以下关键词:"人工智能"、"妇科"、"子宫内膜癌"、"子宫内膜异位症"、"卵巢癌"、"诊断"、"肿瘤妇科",检索时间为 2014 年 2 月至 2024 年 2 月。文章按照 PRISMA 指南进行评估。识别后,在筛选阶段之前,排除重复文章。在筛选阶段,对已确定文章的标题和注释进行分析,以确定是否符合综述主题以及是否有全文版本;在此阶段,不包括科学期刊的摘要和致编辑部的信件。对 685 篇全文进行了资格评估,纳入标准如下:以俄文或英文发表;研究描述了人工智能技术在妇科疾病诊断或治疗中的应用。作者之间的所有分歧均以协商一致的方式解决。最终,80 篇原始资料被纳入本综述。基于人工智能的系统在图像分析和解读方面取得了成功,在过去十年中已成为妇科成像领域革命性的强大工具。在所分析的研究中,人工智能能够提供更快、更准确的预测和诊断,从而提高妇科护理的整体效率。值得注意的是,人工智能不能完全取代医生,但它可以完美地融入临床实践,帮助决策过程,减少鉴别诊断中的错误和不同专家之间互动的差异性。在妇科肿瘤领域,毫无疑问,最有前景的方面之一是可以更好地尤其是早期诊断,并最终提高患者的生存率。迄今为止,人工智能已经取得了巨大成功,预计在未来几年内,人工智能的应用范围还将不断扩大。事实上,要将基于人工智能的技术完全融入临床实践,还有很长的路要走。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An opportunity for using artificial intelligence in modern gynecology
Introduction. Artificial intelligence (AI) is a technology that simulates human brain data processing, its intellectual behavior and critical thinking. Sophisticated AI models can potentially improve patient management by speeding up processes and increasing their accuracy and efficiency at a lower cost of human resources. Compared to other specialties, use of AI in gynecology remains in its infancy. It is important to understand that the available methods for clinical imaging have certain limitations, namely clinician’s workload and data variably interpreted by different doctors. AI, in turn, has the potential to overcome these limitations while increasing diagnostic accuracy.Aim: to structure and analyze current published data on AI use in gynecology.Materials and Methods. A search for primary sources was carried out in the electronic databases PubMed, eLibrary and Google Scholar. The search queries included the following keywords "artificial intelligence", "gynecology", "endometrial cancer", "endometriosis", "ovarian cancer", "diagnostics", "oncogynecology" retrieved from February 2014 to February 2024. Articles were assessed according to PRISMA guidelines. After identification, before the screening stage, duplicates were excluded. At the screening stage, the titles and annotations of the identified articles were analyzed for eligibility to the review topic as well as for available full-text versions; abstracts and letters to the editorial board in scientific journals were excluded at this stage. 685 full-text articles were evaluated for eligibility, the inclusion criteria were as follows: publication in Russian or English; the study describes use of AI technologies in diagnostics or treatment of gynecological diseases. All disagreements between authors were resolved by consensus. Ultimately, 80 primary sources were included in this review.Results. AI-based systems have succeeded in image analyzing and interpreting and over the past decade have become powerful tools that have revolutionized the field of gynecological imaging. In the studies analyzed, AI was able to provide faster and more accurate forecasts and diagnostics, increasing the overall effectiveness of gynecological care. It is important to note that AI cannot fully replace doctors, but it can perfectly integrate into clinical practice, helping in the decision-making process and reducing errors in differential diagnosis and variability of interaction between different specialists. In the field of oncogynecology, undoubtedly one of the most promising aspects is the possibility of better and especially early diagnostics and, ultimately, improved patient survival.Conclusion. A great success has been achieved so far, and AI use is expected to extend in the next few years. In fact, it will take a very long way to go before AI-based technologies are fully integrated into clinical practice.
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