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Development and Trends in Artificial Intelligence in Critical Care Medicine: A Bibliometric Analysis of Related Research over the Period of 2010–2021
Background: The intensive care unit is a center for massive data collection, making it the best field to embrace big data and artificial intelligence. Objective: This study aimed to provide a literature overview on the development of artificial intelligence in critical care medicine (CCM) and tried...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9860734/ https://www.ncbi.nlm.nih.gov/pubmed/36675711 http://dx.doi.org/10.3390/jpm13010050 |
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author | Cui, Xiao Chang, Yundi Yang, Cui Cong, Zhukai Wang, Baocheng Leng, Yuxin |
author_facet | Cui, Xiao Chang, Yundi Yang, Cui Cong, Zhukai Wang, Baocheng Leng, Yuxin |
author_sort | Cui, Xiao |
collection | PubMed |
description | Background: The intensive care unit is a center for massive data collection, making it the best field to embrace big data and artificial intelligence. Objective: This study aimed to provide a literature overview on the development of artificial intelligence in critical care medicine (CCM) and tried to give valuable information about further precision medicine. Methods: Relevant studies published between January 2010 and June 2021 were manually retrieved from the Science Citation Index Expanded database in Web of Science (Clarivate), using keywords. Results: Research related to artificial intelligence in CCM has been increasing over the years. The USA published the most articles and had the top 10 active affiliations. The top ten active journals are bioinformatics journals and are in JCR Q1. Prediction, diagnosis, and treatment strategy exploration of sepsis, pneumonia, and acute kidney injury were the most focused topics. Electronic health records (EHRs) were the most widely used data and the “-omics” data should be integrated further. Conclusions: Artificial intelligence in CCM has developed over the past decade. With the introduction of constantly growing data volume and novel data types, more investigation on artificial intelligence ethics and model correctness and extrapolation should be performed for generalization. |
format | Online Article Text |
id | pubmed-9860734 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-98607342023-01-22 Development and Trends in Artificial Intelligence in Critical Care Medicine: A Bibliometric Analysis of Related Research over the Period of 2010–2021 Cui, Xiao Chang, Yundi Yang, Cui Cong, Zhukai Wang, Baocheng Leng, Yuxin J Pers Med Article Background: The intensive care unit is a center for massive data collection, making it the best field to embrace big data and artificial intelligence. Objective: This study aimed to provide a literature overview on the development of artificial intelligence in critical care medicine (CCM) and tried to give valuable information about further precision medicine. Methods: Relevant studies published between January 2010 and June 2021 were manually retrieved from the Science Citation Index Expanded database in Web of Science (Clarivate), using keywords. Results: Research related to artificial intelligence in CCM has been increasing over the years. The USA published the most articles and had the top 10 active affiliations. The top ten active journals are bioinformatics journals and are in JCR Q1. Prediction, diagnosis, and treatment strategy exploration of sepsis, pneumonia, and acute kidney injury were the most focused topics. Electronic health records (EHRs) were the most widely used data and the “-omics” data should be integrated further. Conclusions: Artificial intelligence in CCM has developed over the past decade. With the introduction of constantly growing data volume and novel data types, more investigation on artificial intelligence ethics and model correctness and extrapolation should be performed for generalization. MDPI 2022-12-27 /pmc/articles/PMC9860734/ /pubmed/36675711 http://dx.doi.org/10.3390/jpm13010050 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Cui, Xiao Chang, Yundi Yang, Cui Cong, Zhukai Wang, Baocheng Leng, Yuxin Development and Trends in Artificial Intelligence in Critical Care Medicine: A Bibliometric Analysis of Related Research over the Period of 2010–2021 |
title | Development and Trends in Artificial Intelligence in Critical Care Medicine: A Bibliometric Analysis of Related Research over the Period of 2010–2021 |
title_full | Development and Trends in Artificial Intelligence in Critical Care Medicine: A Bibliometric Analysis of Related Research over the Period of 2010–2021 |
title_fullStr | Development and Trends in Artificial Intelligence in Critical Care Medicine: A Bibliometric Analysis of Related Research over the Period of 2010–2021 |
title_full_unstemmed | Development and Trends in Artificial Intelligence in Critical Care Medicine: A Bibliometric Analysis of Related Research over the Period of 2010–2021 |
title_short | Development and Trends in Artificial Intelligence in Critical Care Medicine: A Bibliometric Analysis of Related Research over the Period of 2010–2021 |
title_sort | development and trends in artificial intelligence in critical care medicine: a bibliometric analysis of related research over the period of 2010–2021 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9860734/ https://www.ncbi.nlm.nih.gov/pubmed/36675711 http://dx.doi.org/10.3390/jpm13010050 |
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