Subjects: Medicine, Pharmacy >> Clinical Medicine submitted time 2024-01-31 Cooperative journals: 《中国全科医学》
Abstract： Background Currently，the number of research papers on the application of Artificial Intelligence to the field of Alzheimer's disease（AD）has increased significantly. It is important to clarify the latest research hotspots and future development trends in this field. Objective To summarize the relevant research on the application of artificial intelligence to AD through bibliometric analysis，and clarify the research hotspots and trends from 2004 to 2023. Method Literature on the application of artificial intelligence to AD from January 2004 to June 2023 was searched for in the Web of Science core database， and Microsoft Office Excel，CiteSpace，and VOSviewer software were used to visually analyze the number of publications， countries，authors，institutions，keywords，and co-citation networks of the literature. Results Ultimately 3 189 articles were included. The number of literature on the application of artificial intelligence to AD has steadily increased since 2004 and has grown rapidly since 2015，with a maximum of over 600 articles. A total of 94 countries，3 930 institutions，13 563 authors，and 52 019 cited authors participated in this study. Among them，the United States and China were in a leading position in this field；South Korean universities ranked first in terms of the number of publications；In addition，ZHANG DAOQIAG， LIU MINGXIA，SUK HEUNG-IL，and CLIFFORD R. JACK JR were not only prolific authors but also the authors with the most citations. The visualization analysis of keywords and literature citations revealed that regarding the application of artificial intelligence to AD，the diagnosis and disease course classification of AD，as well as the prediction of its risk factors，are current research hotspots and that task analysis are future research trends. Conclusion The application of artificial intelligence to AD has attracted widespread attention from researchers worldwide. The diagnosis and classification of AD，as well as the prediction of its risk factors，are current research hotspots. Developing adjunctive drugs in task analysis，personalized treatment and care， and improving the algorithm performance of artificial intelligence may be research trends in the future.
Subjects: Medicine, Pharmacy >> Preventive Medicine and Hygienics submitted time 2023-11-01 Cooperative journals: 《中国全科医学》
LAI, Honghao
GUO, Jihua
YOU, Liangzhen
WANG, Jiabo
LIU, Cunzhi
LIU, Yue
LIU, Baoli
SUN, Xin
LI, Hui
YANG, Zhongqi
JI, Guang
ZHAO, Linhua
ZHAO, Hui
SHANG, Hongcai
ZENG, Fang
WEI, Xu
ZHANG, Xiaoxiao
GE, Long
Abstract： Background The effective evaluation of scientific and technological achievements in traditional Chinese medicine（TCM） is of great significance in promoting the innovative development of TCM. Previous evaluations of scientific and technological achievements in TCM often used a generalized evaluation method，leading to problems such as inappropriate indicators and limited dimensions，which is not conducive to reflecting the multiple values of achievements in a scientific and comprehensive way. Consequently，there is an urgent need to establish categorized and multi-dimensional evaluation index system for the evaluation of scientific and technological achievements in TCM in the new period. Objective To establish a scientific，categorized，reliable and comprehensive evaluation index system that reflects the principles of TCM and highlights its unique advantages aiming at the scientific and technological achievements in TCM，in accordance with the contemporary requirements for scientific and technological evaluation in China. Methods This study began in November 2022 and was completed in May 2023. A preliminary index framework was developed through literature review and focus group discussions. Delphi expert consultation was then conducted over two rounds to determine the evaluation indexes and points. The hierarchical analysis method was used to calculate the weight of each index. Results The final evaluation index system of scientific and technological achievements in TCM clinical research comprised 10 threshold indicators，4 primary indicators，17 secondary indicators，and 17 evaluation points. After testing，the positive coefficient of experts in both rounds of Delphi method implementation was 100%，the authority coefficient was 0.94 and 0.93，respectively. The Kendall's W consistency test for each level of indicators yielded two-tailed significance（P<0.05），indicated high levels of expert positivity and authority，strong consistency of expert opinion，and reliable consulting results. Conclusion This study constructs a scientific，reasonable，reliable and easy-to-operate evaluation index system for scientific and technological achievements in TCM clinical research. The indexes cover a wide range with highly differentiated weights and TCM characteristics，which is conducive to highlighting the core strengths while comprehensively considering the multiple value of the results. Additionally，the associated evaluation points，enhancing the operationalization of the index system，may potentially serve as a valuable reference for related evaluation activities.
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