Foreign Language Department, Luoyang Institute of Science and Technology, Luoyang, Henan, China.
Foreign Language Department/Language and Cognition Center, Hunan University, Changsha, Hunan, China.
Comput Math Methods Med. 2021 Sep 6;2021:5812499. doi: 10.1155/2021/5812499. eCollection 2021.
Artificial intelligence (AI) is making computer systems capable of executing human brain tasks in many fields in all aspects of daily life. The enhancement in information and communications technology (ICT) has indisputably improved the quality of people's lives around the globe. Especially, ICT has led to a very needy and tremendous improvement in the health sector which is commonly known as electronic health (eHealth) and medical health (mHealth). Deep machine learning and AI approaches are commonly presented in many applications using big data, which consists of all relevant data about the medical health and diseases which a model can access at the time of execution or diagnosis of diseases. For example, cardiovascular imaging has now accurate imaging combined with big data from the eHealth record and pathology to better characterize the disease and personalized therapy. In clinical work and imaging, cancer care is getting improved by knowing the tumor biology and helping in the implementation of precision medicine. The Markov model is used to extract new approaches for leveraging cancer. In this paper, we have reviewed existing research relevant to eHealth and mHealth where various models are discussed which uses big data for the diagnosis and healthcare system. This paper summarizes the recent promising applications of AI and big data in medical health and electronic health, which have potentially added value to diagnosis and patient care.
人工智能(AI)正在使计算机系统能够在日常生活的各个方面执行人类大脑的任务。信息和通信技术(ICT)的增强无疑提高了全球人民的生活质量。特别是,ICT 已经导致医疗保健(eHealth)和医疗保健(mHealth)领域的非常需要和巨大改进。深度学习和人工智能方法通常在使用大数据的许多应用程序中呈现,这些应用程序包含与医疗保健和疾病相关的所有数据,模型在执行或诊断疾病时可以访问这些数据。例如,心血管成像现在结合了来自电子健康记录和病理学的大数据进行精确成像,以更好地描述疾病和个性化治疗。在临床工作和成像中,通过了解肿瘤生物学并帮助实施精准医学,癌症护理得到了改善。马尔可夫模型用于提取利用癌症的新方法。在本文中,我们回顾了与电子健康和移动健康相关的现有研究,其中讨论了各种使用大数据进行诊断和医疗保健系统的模型。本文总结了人工智能和大数据在医疗保健和电子健康中的最新有前途的应用,这些应用有可能为诊断和患者护理增加价值。