With the continuous development of medical image informatics technology, more and more high-throughput quantitative data could be extracted from digital medical images, which has resulted in a new kind of omics-Radiomics. In recent years, in addition to genomics, proteomics and metabolomics, radiomic has attracted the interest of more and more researchers. Compared to other omics, radiomics can be perfectly integrated with clinical data, even with the pathology and molecular biomarker, so that the study can be closer to the clinical reality and more revealing of the tumor development. Mass data will also be generated in this process. Machine learning, due to its own characteristics, has a unique advantage in processing massive radiomic data. By analyzing mass amounts of data with strong clinical relevance, people can construct models that more accurately reflect tumor development and progression, thereby providing the possibility of personalized and sequential treatment of patients. As one of the cancer types whose treatment and diagnosis rely on imaging examination, radiomics has a very broad application prospect in head and neck cancers (HNC). Until now, there have been some notable results in HNC. In this review, we will introduce the concepts and workflow of radiomics and machine learning and their current applications in head and neck cancers, as well as the directions and applications of artificial intelligence in the treatment and diagnosis of HNC.

中文翻译：

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放射组学和机器学习在头颈癌中的应用

随着医学图像信息学技术的不断发展，越来越多的高通量定量数据可以从数字医学图像中提取出来，从而产生了一种新型的组学——放射组学。近年来，除了基因组学、蛋白质组学和代谢组学外，放射组学也引起了越来越多研究人员的兴趣。与其他组学相比，放射组学可以与临床数据完美结合，甚至与病理学和分子生物标志物相结合，使研究更接近临床实际，更能揭示肿瘤的发展。在这个过程中也会产生海量数据。机器学习由于自身的特点，在处理海量放射组学数据方面具有得天独厚的优势。通过分析大量临床相关性强的数据，人们可以构建更准确地反映肿瘤发展和进展的模型，从而为患者的个性化和序贯治疗提供可能。放射组学作为治疗和诊断依赖影像学检查的癌症类型之一，在头颈癌（HNC）中具有非常广阔的应用前景。到目前为止，HNC 已经取得了一些显着的成果。在这篇综述中，我们将介绍放射组学和机器学习的概念和工作流程及其在头颈癌中的应用，以及人工智能在 HNC 治疗和诊断中的方向和应用。放射组学作为治疗和诊断依赖影像学检查的癌症类型之一，在头颈癌（HNC）中具有非常广阔的应用前景。到目前为止，HNC 已经取得了一些显着的成果。在这篇综述中，我们将介绍放射组学和机器学习的概念和工作流程及其在头颈癌中的应用，以及人工智能在 HNC 治疗和诊断中的方向和应用。放射组学作为治疗和诊断依赖影像学检查的癌症类型之一，在头颈癌（HNC）中具有非常广阔的应用前景。到目前为止，HNC 已经取得了一些显着的成果。在这篇综述中，我们将介绍放射组学和机器学习的概念和工作流程及其在头颈癌中的应用，以及人工智能在 HNC 治疗和诊断中的方向和应用。