A Study on Datasets, Risk Factors and Machine Learning Methods Associated with Alzheimer’s Disease

There are several diseases being observed today that were never known before and these diseases are affecting human genes majorly. When we talk about genes, we need to understand that these genes are such biological matter that constitutes an individual. It is a gene that stores the most important matter of a human body called DNA. These genes, which are made up of several DNAs, act as an instructor to the human biological systems. Few of these genes give an instruction to several DNAs to make molecules called proteins. Though very few genes do the production of proteins, those helping in generation of proteins are considered to be important genes. Misfolding of protein leads to neuro-degenerative diseases. Epilepsy, Alzheimer’s disease, Migraines, Strokes, Parkinson’s disease, Multiple Sclerosis are few examples of neurodegenerative diseases. These neurological disorders start due to genetic mutations and the symptoms grow gradually years after years. One of the latest bioscience areas falls in understanding Alzheimer’s disease and the patterns of dementia observed in Alzheimer’s patients. This disease is very uncommon yet very much observed in humans. A study focusing on the available datasets, the associated risk factors and the methods of machine learning that helps in early diagnosis of Alzheimer’s Disease is carried out here.