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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.
Cui, Xiao; Chang, Yundi; Yang, Cui; Cong, Zhukai; Wang, Baocheng; Leng, Yuxin.
  • Cui X; Department of Critical Care Medicine, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing 100191, China.
  • Chang Y; Department of Critical Care Medicine, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing 100191, China.
  • Yang C; Department of Critical Care Medicine, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing 100191, China.
  • Cong Z; Department of Anesthesiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing 100191, China.
  • Wang B; National Science Library, Chinese Academy of Sciences, 33 Beisihuan Xilu, Haidian District, Beijing 100090, China.
  • Leng Y; School of Economics and Management, University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing 100049, China.
J Pers Med ; 13(1)2022 Dec 27.
Article in English | MEDLINE | ID: covidwho-2208601
ABSTRACT

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.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Year: 2022 Document Type: Article Affiliation country: Jpm13010050

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Year: 2022 Document Type: Article Affiliation country: Jpm13010050