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首页> 外文期刊>Nature reviews. Urology >A new era: artificial intelligence and machine learning in prostate cancer
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A new era: artificial intelligence and machine learning in prostate cancer

机译：一个新的时代：前列腺癌中的人工智能和机器学习

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Artificial intelligence (AI)-the ability of a machine to perform cognitive tasks to achieve a particular goal based on provided data-is revolutionizing and reshaping our health-care systems. The current availability of ever-increasing computational power, highly developed pattern recognition algorithms and advanced image processing software working at very high speeds has led to the emergence of computer-based systems that are trained to perform complex tasks in bioinformatics, medical imaging and medical robotics. Accessibility to 'big data' enables the 'cognitive' computer to scan billions of bits of unstructured information, extract the relevant information and recognize complex patterns with increasing confidence. Computer-based decision-support systems based on machine learning (ML) have the potential to revolutionize medicine by performing complex tasks that are currently assigned to specialists to improve diagnostic accuracy, increase efficiency of throughputs, improve clinical workflow, decrease human resource costs and improve treatment choices. These characteristics could be especially helpful in the management of prostate cancer, with growing applications in diagnostic imaging, surgical interventions, skills training and assessment, digital pathology and genomics. Medicine must adapt to this changing world, and urologists, oncologists, radiologists and pathologists, as high-volume users of imaging and pathology, need to understand this burgeoning science and acknowledge that the development of highly accurate AI-based decision-support applications of ML will require collaboration between data scientists, computer researchers and engineers.
机译：人工智能（AI） - 基于提供的数据来实现认知任务的机器执行认知任务的能力 - 正在彻底改变和重塑我们的医疗保健系统。当前，在高速上工作的不断增长的计算能力，高度发达的模式识别算法和高级图像处理软件的可用性导致了培训的基于计算机的系统，以便在生物信息学，医学成像和医疗机器人中执行复杂任务。 “大数据”的可访问性使得“认知”计算机扫描数十亿位的非结构化信息，提取相关信息并随着信心增加识别复杂的模式。基于计算机学习（ML）的计算机的决策支持系统具有通过执行目前分配给专家的复杂任务来彻底改变医学，以提高诊断准确性，提高吞吐量效率，提高临床工作流程，降低人力资源成本并改善治疗选择。这些特征可能对前列腺癌的管理尤其有用，诊断成像，手术干预，技能培训和评估，数字病理学和基因组学中的应用增长。医学必须适应这种不断变化的世界，泌尿科医生，肿瘤学家，放射科学家和病理学家，作为成像和病理学的大批量使用者，需要了解这项蓬勃发展的科学，并承认发展高度准确的基于AI的决策支持ML将需要数据科学家，计算机研究人员和工程师之间的合作。

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