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Computers in Biology and Medicine
Article . 2022 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Research on physical health early warning based on GM(1,1)

Authors: Bo Zeng; Yingjie Yang; Xiaoyi Gou;

Research on physical health early warning based on GM(1,1)

Abstract

At present, hundreds of millions of Chinese people face increasingly serious health risks, and health checks have undoubtedly played a significant role in finding health risks. However, the current health check in China mainly judges the quality of physical functions by a single index value without dynamic analysis of the changing trends of the index, which may lead to unreasonable diagnostic conclusions. In this paper, the data characteristics of physical indicators are systematically analyzed, and grey system models dedicated to data with the characteristics are applied to simulate and predict the changing trends of body indicators. On this basis, possible pathological changes in body organs were identified. Specifically, this paper analyses the state of human kidney functions by grey prediction models. The results showed that even when the renal function index (serum creatinine) is within the normal range, the human renal function might be abnormal. The grey model analysis of the change trends of serum creatinine can predict the potential health hazards of renal functions.

Country
United Kingdom
Related Organizations
Keywords

Grey prediction models, Serum creatinine and renal functions, Data characteristics of physical indicators, Early warning of body lesion trends

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    8
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Top 10%
Average
Top 10%