| Literature DB >> 34939144 |
Zhao-Xia Lu1, Peng Qian1, Dan Bi1, Zhe-Wei Ye2, Xuan He3, Yu-Hong Zhao4, Lei Su1, Si-Liang Li1, Zheng-Long Zhu1.
Abstract
The application of artificial intelligence (AI) technology in the medical field has experienced a long history of development. In turn, some long-standing points and challenges in the medical field have also prompted diverse research teams to continue to explore AI in depth. With the development of advanced technologies such as the Internet of Things (IoT), cloud computing, big data, and 5G mobile networks, AI technology has been more widely adopted in the medical field. In addition, the in-depth integration of AI and IoT technology enables the gradual improvement of medical diagnosis and treatment capabilities so as to provide services to the public in a more effective way. In this work, we examine the technical basis of IoT, cloud computing, big data analysis and machine learning involved in clinical medicine, combined with concepts of specific algorithms such as activity recognition, behavior recognition, anomaly detection, assistant decision-making system, to describe the scenario-based applications of remote diagnosis and treatment collaboration, neonatal intensive care unit, cardiology intensive care unit, emergency first aid, venous thromboembolism, monitoring nursing, image-assisted diagnosis, etc. We also systematically summarize the application of AI and IoT in clinical medicine, analyze the main challenges thereof, and comment on the trends and future developments in this field.Entities:
Keywords: Internet of Things; artificial intelligence; big data; clinical medicine; cloud computing
Mesh:
Year: 2021 PMID: 34939144 PMCID: PMC8693843 DOI: 10.1007/s11596-021-2486-z
Source DB: PubMed Journal: Curr Med Sci ISSN: 2523-899X