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Predicting the clinical citation count of biomedical papers using multilayer perceptron neural network

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成果类型:
期刊论文
作者:
Li, Xin;Tang, Xuli;Cheng, Qikai
通讯作者:
Xuli Tang
作者机构:
[Li, Xin] Huazhong Univ Sci & Technol, Sch Med & Hlth Management, Tongji Med Coll, Wuhan 430030, Hubei, Peoples R China.
[Tang, Xuli] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Hubei, Peoples R China.
[Cheng, Qikai] Wuhan Univ, Sch Informat Management, Wuhan 430074, Hubei, Peoples R China.
通讯机构:
[Xuli Tang] S
School of Information Management, Central China Normal University, Wuhan 430079, Hubei, China
语种:
英文
关键词:
Clinical citation count prediction;Multilayer perceptron neural network;Reference dimension;Biomedical paper
期刊:
Journal of Informetrics
ISSN:
1751-1577
年:
2022
卷:
16
期:
4
页码:
101333
机构署名:
本校为其他机构
院系归属:
信息管理学院
摘要:
The number of clinical citations received from clinical guidelines or clinical trials has been con-sidered as one of the most appropriate indicators for quantifying the clinical impact of biomedical papers. Therefore, the early prediction of clinical citation count of biomedical papers is critical to scientific activities in biomedicine, such as research evaluation, resource allocation, and clinical translation. In this study, we designed a four-layer multilayer perceptron neural network (MPNN) model to predict the clinical citation count of biomedical papers in the future by using 9,822,620 b...

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