Predictive modeling for prognosis in mild cognitive impairment

Jiacheng Li; Jiacheng Huang; Lan Zhou; Wanchun Luo

doi:10.16016/j.1000-5404.201609173

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Predictive modeling for prognosis in mild cognitive impairment

更新时间：2026-01-09

- Predictive modeling for prognosis in mild cognitive impairment
- Journal of Third Military Medical University Vol. 39, Issue 3, Pages: 281-285(2017)
- 作者机构：
- 作者简介：
- 基金信息：
  
  Supported by the Natural Science Foundation of Chongqing(CSTC2013jcyjA10041)
- DOI：10.16016/j.1000-5404.201609173
  CLC：
- Received：27 September 2016，
  
  Published：15 January 2017
- 稿件说明：
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Jiacheng Li, Jiacheng Huang, Lan Zhou, et al. Predictive modeling for prognosis in mild cognitive impairment[J]. Journal of Third Military Medical University, 2017, 39(3): 281-285.
DOI：

Jiacheng Li, Jiacheng Huang, Lan Zhou, et al. Predictive modeling for prognosis in mild cognitive impairment[J]. Journal of Third Military Medical University, 2017, 39(3): 281-285. DOI： 10.16016/j.1000-5404.201609173.

摘要

Abstract

Objective

To establish a predictive model for estimating 24-month prognosis in the patients of mild cognitive impairment based on mathematics.

Methods

Twenty-seven clinical indicators of 152 cases patients with confirmed mild cognitive impairment from the Alzheimer's Disease Neuroimaging Initiative (ADNI

<a href="https://ida.loni.ucla.edu/login.jsp">https://ida.loni.ucla.edu/login.jsp</a>) were collected and analyzed. Bayes discriminant analysis

Decision tree

BP neural network

fuzzy C-means clustering and K-means clustering were used to evaluate the prediction

and the model with higher accuracy was selected.

Results

According to

0.01

6 indicators were selected to establish a diagnostic model by significance test. There were 5 predictive models of estimation established. After 100 times of random sampling for diagnosis simulation in the patients

Bayes discriminant analysis indicated that the average diagnosis accuracy was 74.86%

and the highest accuracy was 84.21%.

Conclusion

Our established model is of high predictive accuracy for 24-month prognosis in mild cognitive impairment.

关键词

Keywords

references

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罗万春阿尔茨海默病和轻度认知损伤诊断的建模分析第三军医大学学报 2013 35 15 1613 1615 http://aammt.tmmu.edu.cn/oa/DArticle.aspx?type=view&id=201304134 罗万春.阿尔茨海默病和轻度认知损伤诊断的建模分析[J].第三军医大学学报, 2013, 35(15): 1613-1615.DOI:10.16016/j.1000-5404.2013.15.027

马翠周先东罗万春阿尔茨海默病和轻度认知损伤诊断的逐步Fisher判别模型第三军医大学学报 2016 38 13 1501 1505 10.16016/j.1000-5404.201509138 马翠, 周先东, 罗万春.阿尔茨海默病和轻度认知损伤诊断的逐步Fisher判别模型[J].第三军医大学学报, 2016, 38(13): 1501-1505. DOI:10.16016/j.1000-5404.201509138

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