Important message: Due to recent site outage we are still restoring full functionality to Authorea powered sites. Please bear with us until full functionality is restored

loading page

Identification of Probable Stages of Alzheimer's disease and its Probability of Occurrence
University of Engineering and Management

Corresponding Author:[email protected]

Author Profile
NSHM Knowledge Campus
Author Profile


Healthcare is an important industry, which offers value-based care to millions of people, while at the same time becoming top revenue earners in many countries. The increasingly growing number of applications of machine learning in healthcare allows us to glimpse at a future where data, analysis, and innovation work hand-in-hand to help countless patients without them ever realizing it. In the fields of healthcare Machine learning is used for imaging and recognition of diseases. Due to the advancing speed Machine learning has gained an adverse field in the diagnostic process of diseases in healthcare. Since machine learning is an algorithm-based field, thus it helps in generating various algorithms based on healthcare and gives great information, ideology and technical abilities to the machines. It also helps in gathering data and follow ups it grips every possible information to develop human life. In this paper, we will compare different classification algorithms with which we can detect whether an individual can get affected by Alzheimer's disease in future or not. It can also detect in which phase the person is at present if the individual is suffering from Alzheimer's disease. Alzheimer is such a disease which cannot be classified or rather identified using any manual procedures. It has some critical values which determines various phases of the disease and the fluctuation of these phases are so sensitive which makes the disease harder to handle manually. We have used the oasis dataset to train the system to make the system responsive to sensitive changes by using classification processes and modified c clustering method which was proposed by us in our previous paper i.e. Brain Anomaly Detection. We have used a pure machine learning process to solve the Alzheimer detection and the probability of Alzheimer detection problem which is recently faced by doctors.