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Introduction|Literature Review|EDA|Models|Summary|Reference

Predictive model for early diagnosis of Alzheimer's Disease using ADNI Databse

Group 18 | Man Liu, Xinan Wang

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Introduction of Alzheimer's Disease

Alzheimer’s disease (AD) is an irreversible neurodegenerative disease that results in a loss of mental function caused by the deterioration of brain tissue. Symptoms includes problems with memory, thinking and behavior. The number of Americans living with Alzheimer's is growing fast. An estimated 5.7 million Americans of all ages have Alzheimer's in 2018, and over 96% are people older than 65 years old and approximately 200,000 individuals under age 65 who have younger-onset Alzheimer's. Alzheimer’s Disease is the only top 10 cause of death in the United States that cannot be prevented, cured or even slowed. MCI, a high-risk condition for dementia, is regarded as a transitional state between cognitive normal (CN) and Alzheimer’s Disease (AD). MCI is also classified as early MCI (EMCI) and late MCI (LMCI).

Introduction of Alzheimer's Disease Neuroimaigng Initiative (ADNI)

ADNI is a global research study that actively supports the investigation and development of treatments that slow or stop the progression of AD. In this multisite longitudinal study, researchers at 63 sites in the US and Canada track the progression of AD in the human brain with clinical, imaging, genetic and biospecimen biomarkers through the process of normal aging, early mild cognitive impairment (EMCI), and late mild cognitive impairment (LMCI) to dementia or AD. The overall goal of ADNI is to validate biomarkers for use in Alzheimer’s disease clinical treatment trials. The goal of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) study is to track the progression of the disease over different disease stages. The study has three phases: ADNI 1 (five years), ADNI GO (two years), and ADNI 2 (five years). We limited our analysis to ADNI1 participants since only patients with early MCI (EMCI) and/or late MCI (LMCI) were enrolled at baseline in ADNIGO and ADNI2

Motivation of Study

Early diagnosis of AD or MCI is really important in the following aspects. First, it could revoke the attention of patients and their family so that additional levels of care and intervention could be given. Second, it could help resource allocation and save time for specific and targeted treatment. Third, it would provide more insights on the treatment of other diseases or combination treatment since most of the AD patients are older than 65 years old and it is very likely they are simultaneously suffering other diseases. Therefore, the aim of this project is to build predictive model for early diagnosis using a wide range of predictors including socio-demographic, clinical, genetic, imaging characteristics, and biospecimen biomarkers.

Problem Statement:

How to early diagnosis disease status?

  1. Solve as a classification problem of classifying disease status, Cognitive Normal, Mild Cognitive Impariment (MCI) Alzheimer's Disease (AD) at an early stage using different classification methods and compare the performance to select an optimal model.