Alzheimer’s Disease Class Prediction by Dynamic Feature Selection and Learning Model: A Review

Authors: Mrs. Shivangi Pandey, Dr. Syed Tanzeem Ahmed

Abstract: Alzheimer's disease is a progressive brain disorder that mainly affects memory. Diagnosing it manually can take a lot of time and is often subject to mistakes because of the large number of patients. Many techniques exist for diagnosing and classifying Alzheimer's, but there is still a strong need for better methods for early detection. This paper looks at different techniques proposed by researchers for classifying the patient report into specific categories. Paper has list various image features used for the disease diagnosis. Different set of image category were also brief used for diagnosis of Alzheimer disease. Finally paper list various evaluation parameters that were used for the comparison of models.

DOI: http://doi.org/10.5281/zenodo.18230625