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人工智能最初在1956年由美国科学家在达特莫斯学会会议上提出,其聚焦于利用机器模拟人的部分思维活动的研究。近年来,人工智能在医疗保健领域取得了众多研究成果,在肿瘤诊断中的应用也得到了蓬勃发展。癌症作为一种自我维持和适应的过程,与其所处的微环境动态相互作用,因此其诊断与治疗极为复杂[1]。现阶段,癌症的诊断多依赖于高分辨率医学成像仪器和病理仪器设备等,由医师对结果加以判断,无法反映成像数据的分布。人工智能则可以对数以万计的图像组成的数据集进行学习及推理,可有效地解决这一问题,使肿瘤诊断从主观感知转向客观科学;另外,人工智能不存在由视觉疲劳、经验不足等主观因素造成的漏诊与误诊。随着人们对自身健康关注度的提升,每天都会并行产生大量与肿瘤相关的医疗数据,人工智能可以对海量的与肿瘤相关的数据进行汇总分析,协助医师高效地开展工作。本文主要从以下几个方面阐述目前人工智能用于肿瘤诊断的新进展。
基于深度学习的人工智能在肿瘤诊断中的应用进展
Advances in the application of artificial intelligence in cancer diagnosis and treatment
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摘要: 随着大数据时代的到来,人工智能得以在医疗领域崭露头角并实现了飞速发展,尤其在肿瘤诊断方面存在巨大潜能。人工智能利用自动化图像分割及提取等关键技术,在实现短时间内对大量肿瘤信息汇总分析的同时,还可以反映现实环境中成像数据的分布,使肿瘤诊断从主观感知转向客观科学,从而高效精确地协助医师的诊断,为诊疗计划的制订和预后的判断提供坚实的基础。笔者拟对人工智能在肿瘤诊断中的关键技术及当前的应用进行综述。Abstract: With the advent of the era of big data, artificial intelligence (AI) has emerged and rapidly developed in the field of medicine. The application of AI has huge potential in achieving prompt and accurate analysis of tumor information aggregation. Moreover, AI can reflect the distribution of imaging data in the real environment by using key technologies, such as automatic image segmentation and extraction. Accordingly, tumor diagnosis can change from subjective perception into objective science. Therefore, AI can assist doctors in efficiently and accurately diagnosing the presence of tumors and providing a solid foundation for the formulation of an appropriate diagnosis plan and informed judgment of the prognosis. This paper reviews the key AI technologies and their current applications in tumor diagnosis.
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