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利用人工智能算法诊断乳腺癌、肺癌和前列腺癌。

Utilization of Artificial Intelligence Algorithms for the Diagnosis of Breast, Lung, and Prostate Cancer.

作者信息

Šebestová Gabriela, Klinger Tomáš, Švajdler Marián, Daum Ondřej, Jirásek Tomáš

出版信息

Cesk Patol. 2025;61(2):70-90.

Abstract

The study focuses on the utilization of artificial intelligence (AI) algorithms in the diagnosis of breast, lung, and prostate cancer. It describes the historical development of the digitalization of pathological processes, the implementation of artificial intelligence, and its current applications in pathology. The study emphasizes machine learning, deep learning, computer vision, and digital pathology, which contribute to the automation and refinement of diagnostics. Special attention is given to specific tools such as the uPath systems from Roche and IBEX Medical Analytics, which enable the analysis of histopathological images, tumor cell classification, and biomarker evaluation. The study also highlights the benefits of AI utilization, including increased diagnostic accuracy and efficiency in laboratory processes, while simultaneously addressing the challenges associated with its implementation, such as ethical and legal considerations, data protection, and liability for errors. The aim of this study is to provide a comprehensive overview of the potential applications of AI in digital pathology and its role in modern oncological diagnostics.

摘要

该研究聚焦于人工智能(AI)算法在乳腺癌、肺癌和前列腺癌诊断中的应用。它描述了病理过程数字化的历史发展、人工智能的实施及其在病理学中的当前应用。该研究强调机器学习、深度学习、计算机视觉和数字病理学,它们有助于诊断的自动化和精细化。特别关注了特定工具,如罗氏公司的uPath系统和IBEX Medical Analytics公司的工具,这些工具能够分析组织病理学图像、进行肿瘤细胞分类和生物标志物评估。该研究还强调了利用AI的好处,包括提高实验室流程中的诊断准确性和效率,同时解决与实施相关的挑战,如伦理和法律考量、数据保护以及错误责任。本研究的目的是全面概述AI在数字病理学中的潜在应用及其在现代肿瘤诊断中的作用。

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