Leite Katia Ramos Moreira, Melo Petronio Augusto de Souza
Laboratory of Medical Investigation, Urology Department, University of São Paulo Medical School, LIM55, Av Dr. Arnando 455, Sao Paulo 01246-903, SP, Brazil.
Diagnostics (Basel). 2024 Oct 14;14(20):2279. doi: 10.3390/diagnostics14202279.
The global population is currently at unprecedented levels, with an estimated 7.8 billion people inhabiting the planet. We are witnessing a rise in cancer cases, attributed to improved control of cardiovascular diseases and a growing elderly population. While this has resulted in an increased workload for pathologists, it also presents an opportunity for advancement. The accurate classification of tumors and identification of prognostic and predictive factors demand specialized expertise and attention. Fortunately, the rapid progression of artificial intelligence (AI) offers new prospects in medicine, particularly in diagnostics such as image and surgical pathology. This article explores the transformative impact of AI in the field of uropathology, with a particular focus on its application in diagnosing, grading, and prognosticating various urological cancers. AI, especially deep learning algorithms, has shown significant potential in improving the accuracy and efficiency of pathology workflows. This comprehensive review is dedicated to providing an insightful overview of the primary data concerning the utilization of AI in diagnosing, predicting prognosis, and determining drug responses for tumors of the urinary tract. By embracing these advancements, we can look forward to improved outcomes and better patient care.
全球人口目前处于前所未有的水平，估计有78亿人居住在这个星球上。我们目睹癌症病例的增加，这归因于心血管疾病控制的改善和老年人口的增加。虽然这给病理学家带来了更多的工作量，但这也带来了进步的机会。肿瘤的准确分类以及预后和预测因素的识别需要专业的专业知识和关注。幸运的是，人工智能（AI）的快速发展为医学带来了新的前景，特别是在图像和外科病理学等诊断领域。本文探讨了人工智能在泌尿病理学领域的变革性影响，特别关注其在诊断、分级和预测各种泌尿系统癌症方面的应用。人工智能，尤其是深度学习算法，在提高病理工作流程的准确性和效率方面显示出巨大潜力。这篇综述致力于提供有关人工智能在诊断、预测预后和确定泌尿道肿瘤药物反应方面应用的主要数据的深入概述。通过采用这些进步，我们可以期待更好的结果和更好的患者护理。
