基于CiteSpace的老年多器官功能障碍综合征可视化分析

Tian Fangjie,Qi Xiaolei,Dong Wei,Zhao Hongliang

兰州大学学报（医学版）（2023）

中国人民解放军医院总医院

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Abstract

目的探究近10年老年多器官功能障碍综合征的研究现状、热点及趋势.方法以Web of Science核心合集数据库为检索对象,利用CiteSpace和Excel对发文量、国家、机构、期刊、关键词、引用次数等统计分析.结果研究产出和引用次数迅速增加,中国产出增速尤为迅猛.中国、美国及其研究机构在该研究领域具备优势.高频关键词依次为 mortality、multiple organ failure、sepsis、management、outcome、risk factor、intensive care unit、trauma、septic shock、epidemiology.近2年突现关键词为 immunosuppression、survival、time、surgery、organ dysfunction、death.结论全球研究热点为epidemiology,sepsis,septic shock,infection,immunosuppression,且关注度呈现上升趋势.2020年新型冠状病毒感染关注度极高.中国发文量居世界前列,但国际合作和影响力有待进一步提高,应进一步对标全球研究热点,加强国际合作,提高学术影响力.

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Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

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