问题C：如何利用大脑结构诊断阿尔茨海默氏病点
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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。其临床特征为 痴呆，包括记忆障碍、失语症、语言障碍、失认症、视觉空间技能障碍、执行功能 障碍、人格和行为改变，其原因尚不清楚。它的特征是进行日常生活活动的能力逐 渐下降，并伴有各种神经精神症状和行为障碍。该疾病通常在老年人中进行性发展 ，并在发病10-20年后因并发症而死亡。
阿尔茨海默病的临床前阶段，也被称为轻度认知障碍 (MCI) ，是一种介于正 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%的患者被 诊断为中度至重度，错过了最佳干预阶段。因此，早期准确诊断阿尔茨海默病和轻 度认知障碍具有重要意义。
附加数据包含特定信息特征4850认知正常老年人 (CN) ，1416例主观记忆投诉 (SMC) ，2968例早期轻度认知障碍 (EMCI) ，5236例晚期轻度认知障碍 (LMCI) 和1738名阿尔茨海默病 (AD) 患者收集在不同的时间点 ( 一个时间点是一个数量) 。请利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，构建阿尔茨 海默病识别模型，设计一种智能诊断方法，准确诊断阿尔茨海默病。
(1)对所附数据的特征指标进行预处理，调查数据特征与阿尔茨海默病诊断之间的 相关性。
(2)利用所附的大脑结构特征和认知行为特征来设计一种阿尔茨海默病的智能诊断
。
(3)首先，将CN、MCI和AD聚为三大类。然后，对于MCI中包含的三个子类 (SMC、 EMCI和LMCI) ，聚类继续细化为三个子类。
(4)附件中相同的样本包含了在不同时间点收集的特征，请分析它们与时间点的关 系，以揭示不同类别疾病随时间的演变模式。
(5)请查阅相关文献，描述CN、SMC、EMCI、LMCI、AD五类患者的早期干预和诊断标 准。
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.
