ADDL: ALZHEIMER'S DISEASE DETECTION USING DEEP LEARNING

Alzheimer's disease (AD) is a devastating, chronic nervous cerebrum condition. Early detection of Alzheimer's disease may aid in timely recovery to prevent brain tissue damage. Experts have abused several mathematical and AI models in the analysis of Alzheimer's disease. Because of the similarities between AD Magnetic Resonance Imaging (MRI) data and normal strong MRI data from more experienced persons, locating AD is difficult. Deep learning approaches have recently shown human-level performance in a variety of areas, including medical image processing. The (ADDL) Alzheimer’s disease detection using deep learning was suggested in this article. New applications and methodologies are needed for breaking down and providing rapid treatment in the initial process. Depending on the patient's diagnosis and disease level, various biomarkers and clinical symptoms are used to determine the progression of Alzheimer's disease. The breakthrough helps aid medication in the recovery and care of people suffering from symptoms and natural properties. These criteria can aid in early medicine, and prediction will prevent the condition from progressing further.