HARISH JAISWAL,JHARNA MAITI,DR. MAHIMA GULATI
DOI: https://doi.org/A complex class of brain disorders known as neurodegenerative diseases is characterized by the progressive loss of neuronal structure and function in particular brain regions. Symptoms of these diseases include memory and cognitive impairment, as well as difficulties carrying out daily tasks. In elderly individuals, Alzheimer's disease usually starts as a slight reduction in cognitive function and develops into serious brain damage. The loss of nerve cells in the hippocampus, a region of the brain, is linked to the pathophysiology of AD. Parkinson's disease is a neurological condition brought on by the loss of nerve cells in the substantia nigra, a part of the brain that controls movement. When these nerve cells degenerate or die, they are unable to produce dopamine, a crucial neurotransmitter.Walking, balancing, speaking, and other coordinated movements are all impacted when dopamine neurons are lost. The disease's primary cause is the death of dopamine-producing neurons in the brain, which impacts bodily functions associated to movement. The proposed model's insights and additional research findings about protein characteristics could be a useful supplement to the current drug discovery process. Bioinformatics study that lowers the high dimensionality of data during disease classification and prediction challenges might benefit from the suggested feature selection techniques and classification procedures.The suggested method can be expanded in the future to categorize and forecast the classes of more brain illnesses brought on by gene changes. In another study, a new DNN-based model is put forth to differentiate AD and MCI patients from cognitively normal people. The network is built with 19 deep layers, drawing inspiration from the original VGG-19.
