The aim of the project is to predict the condition of patients with or without the symptoms of Alzheimer's disease by using machine learning algorithms. An attempt was made to estimate whether a selected patient had this disease. In the project, 2 different algorithms were used, and the algorithm that reached the most accurate result in the fastest way was determined after undergoing training and tests.
In the case of providing the login process in the mobile-based Psychology Prediction application to be developed, the users can enter their age and gender information and see the percentage of the ailment they tend to with the answers they give to the questions asked by the application. The user can also access articles written by expert psychologists and can predict that they will need to consult a specialist accordingly.
• Database normalization
• Logistic Regression Analysis
• Naive Bayes Algorithm
• Evaluation Metrics with Logistic Regression and Naive Bayes(Accuracy,recall,f1-score,sensitivity,specifity)
• 96 percent success rate
##EXPERIMENTAL RESULT AND DISCUSSION
As a result, in this project, which aims to predict whether a person has this disease by using the Alzheimer's disease detection data set, the test results we have carried out using various algorithms and to compare the success rates of these models have been successfully performed. 96 percent success rate