When thinking, memory, and reasoning skills are lost to the point where they interfere with day-to-day tasks, this condition is known as dementia. Various disorders and factors contribute to the development of dementia. Neurodegenerative disorders result in a progressive and irreversible loss of neurons and brain functioning. Currently, there are no cures for these diseases.
The five most common forms of dementia are: • Alzheimer’s disease, It is caused by changes in the brain, including abnormal buildups of proteins, known as amyloid plaques and tau tangles. • Frontotemporal dementia, It is associated with abnormal amounts or forms of the proteins tau and TDP-43. • Lewy body dementia, a form of dementia caused by abnormal deposits of the protein alpha-synuclein, called Lewy bodies. • Vascular dementia, a form of dementia caused by conditions that damage blood vessels in the brain or interrupt the flow of blood and oxygen to the brain. • Mixed dementia, a combination of two or more types of dementia.
Aim and Objectives The aim of this project is to build a machine laerning model to predict chances that a person will have dementia and the probable type they can have in order to bridge the barriers to diagnosis and care. The specific objectives includes: • Data gathering from a public repository (kaggle) • Data preparation and transformation • Training a machine learning model on the prepared and transformed data • Evaluation of the model performance • Deployment of the model for use by the public
Methodology (Flow Process)
Problem Statement As the seventh leading cause of mortality and one of the main causes of disability and dependency among older people worldwide, dementia is frequently unrecognized and misunderstood, which leads to stigmatization and barriers to diagnosis and care. Data Collection and Description The data was collected from a public repository Kaggle and the dataset description is as follows: