George Rose S, Htoo Arkar, Cheng Michael, Masterson Timothy M, Huang Kun, Adra Nabil, Kaimakliotis Hristos Z, Akgul Mahmut, Cheng Liang
Department of Pathology and Laboratory Medicine, Albany Medical Center, Albany, NY.
Department of Medicine, Indianapolis, Indianapolis, IN.
Urol Oncol. 2022 Jun;40(6):262-270. doi: 10.1016/j.urolonc.2022.03.003. Epub 2022 Apr 13.
Multiple novel modalities tasking artificial intelligence based computational pathology applications and integrating other variables, such as risk factors, tumor microenvironment, genomic testing data, laboratory findings, clinical history, and radiology findings, will improve diagnostic consistency and generate a synergistic diagnostic workflow. In this article, we present the concise and contemporary review on the utilization of artificial intelligence in prostate cancer and identify areas for possible future applications.
多种基于人工智能的新型计算病理学应用模式以及整合其他变量（如风险因素、肿瘤微环境、基因组检测数据、实验室检查结果、临床病史和放射学检查结果），将提高诊断的一致性并产生协同的诊断工作流程。在本文中，我们对人工智能在前列腺癌中的应用进行了简明且与时俱进的综述，并确定了未来可能的应用领域。
