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Application of AI and IoT in Clinical Medicine: Summary and Challenges
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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Huazhong University of Science and Technology
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8693843/ https://www.ncbi.nlm.nih.gov/pubmed/34939144 http://dx.doi.org/10.1007/s11596-021-2486-z |
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author | Lu, Zhao-xia Qian, Peng Bi, Dan Ye, Zhe-wei He, Xuan Zhao, Yu-hong Su, Lei Li, Si-liang Zhu, Zheng-long |
author_facet | Lu, Zhao-xia Qian, Peng Bi, Dan Ye, Zhe-wei He, Xuan Zhao, Yu-hong Su, Lei Li, Si-liang Zhu, Zheng-long |
author_sort | Lu, Zhao-xia |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8693843 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Huazhong University of Science and Technology |
record_format | MEDLINE/PubMed |
spelling | pubmed-86938432021-12-22 Application of AI and IoT in Clinical Medicine: Summary and Challenges Lu, Zhao-xia Qian, Peng Bi, Dan Ye, Zhe-wei He, Xuan Zhao, Yu-hong Su, Lei Li, Si-liang Zhu, Zheng-long Curr Med Sci Article 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. Huazhong University of Science and Technology 2021-12-22 2021 /pmc/articles/PMC8693843/ /pubmed/34939144 http://dx.doi.org/10.1007/s11596-021-2486-z Text en © Huazhong University of Science and Technology 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Lu, Zhao-xia Qian, Peng Bi, Dan Ye, Zhe-wei He, Xuan Zhao, Yu-hong Su, Lei Li, Si-liang Zhu, Zheng-long Application of AI and IoT in Clinical Medicine: Summary and Challenges |
title | Application of AI and IoT in Clinical Medicine: Summary and Challenges |
title_full | Application of AI and IoT in Clinical Medicine: Summary and Challenges |
title_fullStr | Application of AI and IoT in Clinical Medicine: Summary and Challenges |
title_full_unstemmed | Application of AI and IoT in Clinical Medicine: Summary and Challenges |
title_short | Application of AI and IoT in Clinical Medicine: Summary and Challenges |
title_sort | application of ai and iot in clinical medicine: summary and challenges |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8693843/ https://www.ncbi.nlm.nih.gov/pubmed/34939144 http://dx.doi.org/10.1007/s11596-021-2486-z |
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