Paper Title
Alzheimer's Disease Diagnosis and Classification Using a Novel Machine-Learning Algorithm

Abstract
Alzheimer's disease has emerged as a serious health concern in recent years. Alzheimer's disease is characterized by memory loss, altered behavior, and inability to care for oneself. In light of this, we need to investigate this issue as soon as possible, before it gets worse and causes actual damage. In the early stages of Alzheimer's disease, patients often experience a decline in their short-term memory. There may also be depression and a general disinterest in living.Algorithms such as logical regression,Random forest, Decision Tree,SVM and Novel Algorithm are being used in this paper with their results and Graphs. Using the retrieved features, a trained model is generated and input into a Novel Algorithm. The Diagnosis and Classification of Alzheimer Disease Using Novel Machine Learning Algorithm attained an accuracy of 99.38%.To identify and diagnose Alzheimer's disease, a number of Machine Learning approaches have been used. This discovery will help medical practitioners recognise Alzheimer's disease at an early stage in the future, allowing patients to be protected from the condition before it becomes severe. Keywords - Machine Learning Algorithm, Alzheimer’s Disease, Scikit-Learn, Python