An approximation to the risk factors linked to alzheimer’s disease
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Keywords
P-value, Alzheimer, risk factors, scrum, artificial intelligent, machine learning, dataset
Abstract
The objective of this project is to develop an application that integrates AI, machine learning and cloud computing technologies to reduce the user’s chances of suffering from Alzheimer’s disease in the future. The expectations regarding the application include that it can collect data about the most common risk factors in Alzheimer patients such as education level, hormonal and nutritional levels and lifestyle habits (smoking, sedentary lifestyle, alcohol, etc.) to prevent Alzheimer. It is also expected that it can determine the level of danger and the main risk factors that the user should be aware of. This software will keep running in cloud computing to ensure that it is always synchronized with the databases containing the factors described above, such as MEDLINE, PubMed, AlzForum (ALZRISK) and ADNI. The latter collects different data sources such as AIBL and DoD-ADNI. It was found that the main risk factors that increase the probability of suffering the disease are: being overweight with a maximum value of 0.5 p-value when the diet followed is not balanced. A value of 0.3 p-value indicates that the diet is not followed. A deficit in physical activity is related to a p-value of 0.11. The years of formal studies also contribute by a significant value of 0.008 when said years are between 0 and 5. Stress from work can contribute with a maximum value of 0.006.
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