2022年数维杯国际赛C题翻译

2022_“ShuWei Cup” 

Problem C：How to Diagnose Alzheimer's Disease Using Brain Structural Features and Cognitive Behavioral Features 

        Alzheimer's disease (AD) is a progressive neurodegenerative disease with an insidious onset. It is characterized clinically by a full spectrum of dementia, including memory impairment, aphasia, dysfluency, agnosia, impairment of visuospatial skills, executive dysfunction, and personality and behavioral changes, the cause of which is still unknown. It is characterized by a progressive decline in the ability to perform activities of daily living,with various neuropsychiatric symptoms and behavioral disturbances. The disease is usually progressive in the elderly, with progressive loss of independent living skills and death from complications 10 to 20 years after the onset of the disease. 

        The preclinical stage of Alzheimer's disease, also known as mild cognitive impairment (MCI), is a transitional state between normal and severe. Due to the limited cognition of the disease by patients and their families, 67% of patients were diagnosed as moderate to severe and had missed the best intervention stage. Therefore, early and accurate diagnosis of Alzheimer's disease and mild cognitive impairment is of great significance. 

        The attached data contain specific information characteristics of 4850 cognitive normal elderly (CN), 1416 patients with subjective memory complaint (SMC), 2968 patients with early mild cognitive impairment (EMCI), 5236 patients with late mild cognitive impairment (LMCI) and 1738 patients with Alzheimer's disease (AD) collected at different time points (one time point is a quantity). Please use the brain structural characteristics and cognitive behavioral characteristics of the different categories of people provided in the Appendix to construct an Alzheimer's disease identification model and design an intelligent diagnostic method to accurately diagnose Alzheimer's disease. 

(1)Preprocess the characteristic indicators of the attached data to investigate the correlation between data characteristics and the diagnosis of Alzheimer's disease. 

(2)Use the attached structural brain features and cognitive behavioral features to design an intelligent diagnosis of Alzheimer's disease. 

(3)First, cluster CN, MCI and AD into three major classes. Then, for the three subclasses contained in MCI (SMC, EMCI, and LMCI), the clustering was continued to be refined into three subclasses. 

(4)The same sample in the annex contains features collected at different time points, please analyze them in relation to the time points to uncover patterns in the evolution of different categories of diseases over time. 

(5)Please consult the relevant literature to describe the early intervention and diagnostic criteria for the five categories of CN, SMC, EMCI, LMCI, and AD.

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问题C：如何使用大脑结构诊断阿尔茨海默病特征和认知行为特征

        阿尔茨海默病(AD)是一种进行性神经退行性疾病发病隐匿。它的临床特征是全方位的痴呆，包括记忆障碍、失语症、流利性障碍、失认症、视觉空间技能障碍、执行功能障碍以及性格和行为改变，其原因是仍然未知。其特点是执行能力逐渐下降日常生活活动，具有各种神经精神症状和行为干扰。这种疾病通常在老年人中进行性独立生活技能与发病后10至20年并发症死亡该病的发病率。

        阿尔茨海默病的临床前阶段，也称为轻度认知损伤(MCI)是正常和严重之间的过渡状态。由于患者及其家属对该疾病的认知有限，67%的患者诊断为中度至重度，错过了最佳干预阶段。因此，阿尔茨海默病和轻度认知障碍的早期准确诊断是具有重要意义。

        所附数据包含在不同时间点收集的4850名认知正常老年人(CN)、1416名主观记忆障碍患者(SMC)、2968名早期轻度认知障碍患者(EMCI)、5236名晚期轻度认知障碍(LMCI)和1738名阿尔茨海默病患者(AD)的特定信息特征(一个时间点是一个数量)。请使用附录中提供的不同类别人群的大脑结构特征和认知行为特征来构建阿尔茨海默病识别模型，并设计智能诊断方法来准确诊断阿尔茨海默病。

(1)预处理所附数据的特征指标，以调查数据特征与阿尔茨海默病诊断之间的相关性。

(2)利用附加的大脑结构特征和认知行为特征来设计阿尔茨海默病的智能诊断。

(3)首先，将CN、MCI和AD分为三大类。然后，对于MCI中包含的三个子类(SMC、EMCI和LMCI)，继续将聚类细化为三个子类。

(4)附件中的同一样本包含在不同时间点收集的特征，请根据时间点对其进行分析，以揭示不同类别疾病随时间演变的模式。

(5)请查阅相关文献，描述CN、SMC、EMCI、LMCI和AD五类疾病的早期干预和诊断标准。