Predictive modeling of the severity/progression of alzheimer's diseases

R. Qiu, Jason L. Qiu, Y. Badr
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引用次数: 8

Abstract

Alzheimer's disease (AD) cannot be cured or slowed down with today's medication. Scientific studies have found that 1) the progression of AD is highly correlated to a cognition decline, 2) cognition drop is a precursor of Alzheimer's disease, and 3) making lifestyle changes and training the brain can slow down AD progression. This project aims to develop a predictive model to know the progression of an AD patient. Factors that influence the disease's severity and progression are determined, which would help facilitate developing a set of personalized care instructions to guide individuals in making the necessary lifestyle choices to retain or rejuvenate their brain's cognitive ability. Ultimately, the developed model can be potentially incorporated into a convenient self-diagnostic tool for the public to use at home.
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阿尔茨海默病严重程度/进展的预测模型
阿尔茨海默病(AD)不能用今天的药物治愈或减缓。科学研究发现,1)阿尔茨海默病的进展与认知能力下降高度相关,2)认知能力下降是阿尔茨海默病的前兆,3)改变生活方式和训练大脑可以减缓阿尔茨海默病的进展。本项目旨在开发一种预测模型来了解AD患者的病情进展。确定了影响疾病严重程度和进展的因素,这将有助于制定一套个性化的护理指导,指导个人做出必要的生活方式选择,以保持或恢复大脑的认知能力。最终,开发的模型可能会被纳入一个方便的自我诊断工具,供公众在家中使用。
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Several problems need to be studied in grey system theory Predictive modeling of the severity/progression of alzheimer's diseases Uniform incidence degree and its properties A decision model of three — Endpoint interval method based on grey theory Construction and application of performance evaluation system for Chinese pharmaceutical manufacturing industry from stakeholders' perspective
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